Physiologically Based Pharmacokinetic Modeling for Olaparib Dosing Recommendations: Bridging Formulations, Drug Interactions, and Patient Populations

Improving olaparib exposure to optimize adverse effects management

Background

Olaparib is an inhibitor of the human poly-(ADP-ribose)-polymerase enzymes (PARP1/2) needed to repair single-strand DNA breaks. It is used in breast, ovarian, prostate and pancreatic cancer.

Objectives

This work aimed to describe the pharmacokinetics/pharmacodynamics (PK/PD) relationship between olaparib plasma concentrations and common adverse effects (i.e. anaemia and hypercreatininaemia), in a real-life setting, to propose a target concentration for therapeutic drug monitoring.

Methods

Two PK/PD models describing the evolution of haemoglobinaemia and creatininaemia as a function of time were developed, based on data from, respectively, 38 and 37 patients receiving olaparib. The final model estimates were used to calculate the incidence of anaemia and creatinine increase according to plasma trough concentrations for 1000 virtual subjects to define target exposure.

Results

The final models correctly described the temporal evolution of haemoglobinaemia and creatininaemia for all patients. The haemoglobinaemia PK/PD model is inspired by Friberg's model, and the creatininaemia PK/PD model is an indirect response model. Model parameters were in agreement with physiological values and close to literature values for similar models. The mean (population) plasma haemoglobin concentration at treatment initiation, as estimated by the model, was 11.62 g/dL, while creatinine concentration was 71.91 µmol/L. Using simulations, we have identified a target trough concentration of 3500-4000 ng/mL, above which more than 20% of patients would report grade ≥3 anaemia.

Conclusion

Based on real-world data, we were able to properly describe the time course of haemoglobinaemia and plasma creatininaemia during olaparib treatment.

Dosage optimization for reducing tumor burden using a phenotype-structured population model with a drug-resistance continuum

Drug resistance is a significant obstacle to effective cancer treatment. To gain insights into how drug resistance develops, we adopted a concept called fitness landscape and employed a phenotype-structured population model by fitting to a set of experimental data on a drug used for ovarian cancer, olaparib. Our modeling approach allowed us to understand how a drug affects the fitness landscape and track the evolution of a population of cancer cells structured with a spectrum of drug resistance. We also incorporated pharmacokinetic (PK) modeling to identify the optimal dosages of the drug that could lead to long-term tumor reduction. We derived a formula that indicates that maximizing variation in plasma drug concentration over a dosing interval could be important in reducing drug resistance. Our findings suggest that it may be possible to achieve better treatment outcomes with a drug dose lower than the levels recommended by the drug label. Acknowledging the current limitations of our work, we believe that our approach, which combines modeling of both PK and drug resistance evolution, could contribute to a new direction for better designing drug treatment regimens to improve cancer treatment.

Evaluation of the potential impact on pharmacokinetics of various cytochrome P450 substrates of increasing IL-6 levels following administration of the T-cell bispecific engager glofitamab

Glofitamab is a novel T cell bispecific antibody developed for treatment of relapsed-refractory diffuse large B cell lymphoma and other non-Hodgkin's lymphoma indications. By simultaneously binding human CD20-expressing tumor cells and CD3 on T cells, glofitamab induces tumor cell lysis, in addition to T-cell activation, proliferation, and cytokine release. Here, we describe physiologically-based pharmacokinetic (PBPK) modeling performed to assess the impact of glofitamab-associated transient increases in interleukin 6 (IL-6) on the pharmacokinetics of several cytochrome P450 (CYP) substrates. By refinement of a previously described IL-6 model and inclusion of in vitro CYP suppression data for CYP3A4, CYP1A2, and 2C9, a PBPK model was established in Simcyp to capture the induced IL-6 levels seen when glofitamab is administered at the intended dose and dosing regimen. Following model qualification, the PBPK model was used to predict the potential impact of CYP suppression on exposures of various CYP probe substrates. PBPK analysis predicted that, in the worst-case, the transient elevation of IL-6 would increase exposures of CYP3A4, CYP2C9, and CYP1A2 substrates by less than or equal to twofold. Increases for CYP3A4, CYP2C9, and CYP1A2 substrates were projected to be 1.75, 1.19, and 1.09-fold following the first administration and 2.08, 1.28, and 1.49-fold following repeated administrations. It is recommended that there are no restrictions on concomitant treatment with any other drugs. Consideration may be given for potential drug-drug interaction during the first cycle in patients who are receiving concomitant CYP substrates with a narrow therapeutic index via monitoring for toxicity or for drug concentrations.

Pediatric oncology drug development and dosage optimization

Oncology drug discovery and development has always been an area facing many challenges. Phase 1 oncology studies are typically small, open-label, sequential studies enrolling a small sample of adult patients (i.e., 3-6 patients/cohort) in dose escalation. Pediatric evaluations typically lag behind the adult development program. The pediatric starting dose is traditionally referenced on the recommended phase 2 dose in adults with the incorporation of body size scaling. The size of the study is also small and dependent upon the prevalence of the disease in the pediatric population. Similar to adult development, the dose is escalated or de-escalated until reaching the maximum tolerated dose (MTD) that also provides desired biological activities or efficacy. The escalation steps and identification of MTD are often rule-based and do not incorporate all the available information, such as pharmacokinetic (PK), pharmacodynamic (PD), tolerability and efficacy data. Therefore, it is doubtful if the MTD approach is optimal to determine the dosage. Hence, it is important to evaluate whether there is an optimal dosage below the MTD, especially considering the emerging complexity of combination therapies and the long-term tolerability and safety of the treatments. Identification of an optimal dosage is also vital not only for adult patients but for pediatric populations as well. Dosage-finding is much more challenging for pediatric populations due to the limited patient population and differences among the pediatric age range in terms of maturation and ontogeny that could impact PK. Many sponsors defer the pediatric strategy as they are often perplexed by the challenges presented by pediatric oncology drug development (model of action relevancy to pediatric population, budget, timeline and regulatory requirements). This leads to a limited number of approved drugs for pediatric oncology patients. This review article provides the current regulatory landscape, incentives and how they impact pediatric drug discovery and development. We also consider different pediatric cancers and potential clinical trial challenges/opportunities when designing pediatric clinical trials. An outline of how quantitative methods such as pharmacometrics/modelling & simulation can support the dosage-finding and justification is also included. Finally, we provide some reflections that we consider helpful to accelerate pediatric drug discovery and development.

Development of a simple high-performance liquid chromatography-ultraviolet detection method for olaparib in patients with ovarian cancer

Olaparib is a small-molecule inhibitor of poly(ADP)-ribose polymerase (PARP) used as maintenance therapy for recurrent ovarian cancer and newly diagnosed advanced ovarian cancer after initial chemotherapy. An exposure-toxicity correlation has been reported between the probability of anemia, a common adverse event associated with olaparib, and the steady-state minimum plasma concentration (Cmin) as well as the predicted maximum plasma concentration (Cmax). On the other hand, olaparib exhibits high interpatient variability with regard to the area under the concentration-time curve, Cmax, and Cmin. Therefore, we developed a simple and sensitive assay based on high-performance liquid chromatography with ultraviolet light (HPLC-UV) for the therapeutic drug monitoring of olaparib. The analysis was performed on an octadecylsilyl column with a mobile phase consisting of 0.5% KH2PO4 (pH 4.5) and acetonitrile (71:29, v/v), at a flow rate of 0.8 mL/min. Olaparib and an internal standard (imatinib) were well separated from the co-extracted material, with retention times of 13.6 and 11.5 min, respectively. The calibration curve for olaparib showed linearity over the concentration range of 0.10-10.0 μg/mL (r2 = 0.9998). The intra- and inter- day validation coefficients ranged from 1.79 to 4.13% and 1.37 to 3.55%, respectively. Measurement accuracy ranged from - 6.07 to 3.26%, with a recovery rate of more than 91.06%. The developed method was then applied to evaluate the plasma olaparib concentrations in patients with ovarian cancer. Our findings demonstrate that HPLC-UV is an economical, simple, and sensitive method for clinical application and holds promise for the effective drug monitoring of olaparib during ovarian cancer treatment.

Bidirectional pharmacokinetic drug interactions between olaparib and metformin

OBJECTIVE

Olaparib is a PARP (poly-ADP-ribose polymerase) inhibitor used for maintenance therapy in BRCA-mutated cancers. Metformin is a first-choice drug used in the treatment of type 2 diabetes. Both drugs are commonly co-administered to oncologic patients with add-on type 2 diabetes mellitus. Olaparib is metabolized by the CYP3A4 enzyme, which may be inhibited by metformin through the Pregnane X Receptor. In vitro studies have shown that olaparib inhibits the following metformin transporters: OCT1, MATE1, and MATE2K. The aim of the study was to assess the influence of 'the perpetrator drug' on the pharmacokinetic (PK) parameters of 'the victim drug' after a single dose. To evaluate the effect, the AUC0→∞ (area under the curve) ratio was determined (the ratio between AUC0→∞ in the presence of the perpetrator and AUC0→∞ without the presence of the perpetrator).

METHODS

Male Wistar rats were assigned to three groups (eight animals in each group), which were orally administered: metformin and olaparib (IMET+OLA), vehiculum with metformin (IIMET), and vehiculum with olaparib (IIIOLA). Blood samples were collected after 24 h. HPLC was applied to measure the concentrations of olaparib and metformin. The PK parameters were calculated in a non-compartmental model.

RESULTS

Metformin did not affect the olaparib PK parameters. The AUC0→∞ IMET+OLA/IIIOLA ratio was 0.99. Olaparib significantly increased the metformin Cmax (by 177.8%), AUC0→t (by 159.8%), and AUC0→∞ (by 74.1%). The AUC0→∞ IMET+OLA/IIMET ratio was 1.74.

CONCLUSIONS

A single dose of metformin did not affect the PK parameters of olaparib, nor did it inhibit the olaparib metabolism, but olaparib significantly changed the metformin pharmacokinetics, which may be of clinical importance.

Application of physiologically based pharmacokinetics modeling in the research of small-molecule targeted anti-cancer drugs

INTRODUCTION

Physiologically based pharmacokinetics (PBPK) models are increasingly used in the drug research and development, especially in anti-cancer drugs. Between 2001 and 2020, a total of 89 small-molecule targeted antitumor drugs were approved in China and the United States, some of which already included PBPK modeling in their application or approval packages. This article intended to review the prevalence and application of PBPK model in these drugs.

METHOD

Article search was performed in the PubMed to collect English research articles on small-molecule targeted anti-cancer drugs using PBPK modeling. The selected articles were classified into nine categorizes according to the application areas and further analyzed.

RESULT

From 2001 to 2020, more than 60% of small-molecule targeted anti-cancer drugs (54/89) were studied using PBPK model with a wide range of application. Ninety research articles were included, of which 48 involved enzyme-mediated drug-drug interaction (DDI). Of these retrieved articles, Simcyp, GastroPlus, and PK-Sim were the most widely model building platforms, which account for 63.8%, 15.2%, and 8.6%, respectively.

CONCLUSION

PBPK modeling is commonly and widely used to research small-molecule targeted anti-cancer drugs.

Inhibition of efflux transporters by poly ADP-ribose polymerase inhibitors

Poly ADP-ribose polymerase (PARP) inhibitors have been approved for the treatment of various cancers. They share a similar mechanism of action but have differences in pharmacokinetic characteristics and potential for drug-drug interactions (DDI). This study evaluated the potential ATP-binding cassette transporter-mediated interactions between PARP inhibitors (niraparib, olaparib and rucaparib) and statins (atorvastatin and rosuvastatin). We studied the inhibitory activity of PARP inhibitors on breast cancer resistance protein (BCRP), multidrug resistance-associated protein 3 (MRP3) and P-glycoprotein (P-gp) using vesicular transport assays and determined the concentrations required for 50% inhibition (IC50 ). Then, we predicted the increase of statin exposure followed by the administration of PARP inhibitors using a mechanistic static model. Rucaparib was the strongest inhibitor of BCRP-mediated rosuvastatin transport (IC50 13.7 μM), followed by niraparib (42.6 μM) and olaparib (216 μM). PARP inhibitors did not affect MRP3. While niraparib appeared to inhibit P-gp, the inhibition showed large variability. The inhibition of intestinal BCRP by rucaparib, niraparib and olaparib was predicted to elevate rosuvastatin exposure by 52%, 37% and 24%, respectively. The interactions between PARP inhibitors and rosuvastatin are probably of minor clinical significance alone, but combined with other predisposing factors, they may increase the risk of rosuvastatin-associated adverse effects.

Physiologically-based pharmacokinetic modeling for optimal dosage prediction of olaparib when co-administered with CYP3A4 modulators and in patients with hepatic/renal impairment

This study aimed to develop a physiologically-based pharmacokinetic (PBPK) model to predict the maximum plasma concentration (Cmax) and trough concentration (Ctrough) at steady-state of olaparib (OLA) in Caucasian, Japanese and Chinese. Furthermore, the PBPK model was combined with mean and 95% confidence interval to predict optimal dosing regimens of OLA when co-administered with CYP3A4 modulators and administered to patients with hepatic/renal impairment. The dosing regimens were determined based on safety and efficacy PK threshold Cmax (< 12,500 ng/mL) and Ctrough (772-2500 ng/mL). The population PBPK model for OLA was successfully developed and validated, demonstrating good consistency with clinically observed data. The ratios of predicted to observed values for Cmax and Ctrough fell within the range of 0.5 to 2.0. When OLA was co-administered with a strong or moderate CYP3A4 inhibitor, the recommended dosing regimens should be reduced to 100 mg BID and 150 mg BID, respectively. Additionally, the PBPK model also suggested that OLA could be not recommended with a strong or moderate CYP3A4 inducer. For patients with moderate hepatic and renal impairment, the dosing regimens of OLA were recommended to be reduced to 200 mg BID and 150 mg BID, respectively. In cases of severe hepatic and renal impairment, the PBPK model suggested a dosing regimen of 100 mg BID for OLA. Overall, this present PBPK model can determine the optimal dosing regimens for various clinical scenarios involving OLA.

Ovarian cancer in the older patient: where are we now? What to do next?

In recent years, major advances have been made toward the individualization of epithelial ovarian cancer care, leading to an overall improvement of patient outcomes. However, real-life data indicate that the oldest populations do not benefit from this, due to aspects related to cancer (more aggressive histopathological features), treatment (i.e. frequently suboptimal), and the host (increased toxicities in patients with lower physiological reserve). A specific risk-benefit perspective should therefore be taken when considering surgery, chemotherapy, and maintenance treatments: the decision for cytoreductive surgery should include geriatric vulnerability and surgical complexity, neo-adjuvant chemotherapy being an option when primary surgery appears at high risk; carboplatin paclitaxel association remains the standard even in vulnerable older patients; and bevacizumab and poly(ADP-ribose) polymerase inhibitors maintenance are interesting options provided they are prescribed according to their indications with a close monitoring of their toxicities. Future studies should aim to individualize care without limiting access of older patients to innovation. A specific focus is needed on age-specific translational analyses (focusing on tumor mutational burden and impaired biological pathways), a better patient stratification according to geriatric parameters, an adaptation of both oncological treatment and geriatric interventions, and treatment adaptations not a priori but according to formal pharmacokinetic data.

Revisiting the in-vitro and in-vivo considerations for in-silico modelling of complex injectable drug products

Complex injectable drug products (CIDPs) have often been developed to modulate the pharmacokinetics along with efficacy for therapeutic agents used for remediation of chronic disorders. The effective development of CIDPs has exhibited complex kinetics associated with multiphasic drug release from the prepared formulations. Consequently, predictability of pharmacokinetic modelling for such CIDPs has been difficult and there is need for advanced complex computational models for the establishment of accurate prediction models for in-vitro-in-vivo correlation (IVIVC). The computational modelling aims at supplementing the existing knowledge with mathematical equations to develop formulation strategies for generation of predictable and discriminatory IVIVC. Such an approach would help in reduction of the burden of effect of hidden factors on preclinical to clinical translations. Computational tools like physiologically based pharmacokinetics (PBPK) modelling have combined physicochemical and physiological properties along with IVIVC characteristics of clinically used formulations. Such techniques have helped in prediction and understanding of variability in pharmacodynamic parameters of potential generic products to clinically used formulations like Doxil®, Ambisome®, Abraxane® in healthy and diseased population using mathematical equations. The current review highlights the important formulation characteristics, in-vitro, preclinical in-vivo aspects which need to be considered while developing a stimulatory predictive PBPK model in establishment of an IVIVC and in-vitro-in-vivo relationship (IVIVR).

Another Step Toward Qualification of Pediatric Physiologically Based Pharmacokinetic Models to Facilitate Inclusivity and Diversity in Pediatric Clinical Studies

Robust prediction of pharmacokinetics (PKs) in pediatric subjects of diverse ages, ethnicities, and morbidities is critical. Qualification of pediatric physiologically-based pharmacokinetic (P-PBPK) models is an essential step toward enabling precision dosing of these vulnerable groups. Twenty-two manuscripts involving P-PBPK predictions and corresponding observed PK data (e.g., area under the curve and clearance) for 22 small-molecule compounds metabolized by CYP (3A4, 1A2, and 2C9), UGT (1A9 and 2B7), FMO3, renal, non-renal, and complex routes were identified; ratios of mean predicted/observed (P/O) PK parameters were calculated. Seventy-eight of 115 mean predicted PK parameters were within 0.8 to 1.25-fold of observed data, 98 within 0.67 to 1.5-fold, 109 within 2-fold, and only 6 P/O ratios were outside of these bounds. A set of 12 CYP3A4-metabolized compounds and a set of 6 metabolized by other enzymes, CYP1A2 (1 compound), CYP2C9 (2 compounds), UGT1A9 (1 compound) and UGT2B7 (2 compounds) had 56 of 59 and 22 of 25 mean P/O ratios, respectively, that fell within the > 0.5 and < 2.0-fold boundaries. For compounds covering renal, non-renal, complex, and FM03 routes of elimination, 29 of 31 mean P/O ratios fell within the 0.67 to 1.5-fold bounds, including 4 of 5 P/O ratios from newborns. P-PBPK modeling and simulation is a strategic component of the complement of precision dosing methods and has a vital role to play in dose adjustment in vulnerable pediatric populations, such as those with disease or in different ethnic groups. Qualification of such models is an essential step toward acceptance of this methodology by regulators.

Effect of a moderate CYP3A inducer efavirenz on the pharmacokinetics of fuzuloparib: An open-label, fixed sequence study in Chinese healthy male subjects

To evaluate the potential drug-drug interaction (DDI), safety and tolerability of fuzuloparib co-administered with a moderate CYP3A inducer efavirenz in healthy male subjects. Eighteen healthy male subjects were enrolled in a single-center, single-arm, open-label, fixed-sequence study. Fuzuloparib was administered as a single oral 50 mg under a fasting state on day 1, efavirenz (600 mg once daily) was given on days 4-17 before bed time, concomitantly with fuzuloparib on day 18, and for the follow-up 3 additional days (days 19-20). Pharmacokinetic sampling was performed following each fuzuloparib dose. Safety and tolerability were assessed during the whole process via clinical laboratory tests. Ratios of least-squares means (GMRs) and 90% geometric confidence interval (90% CI) of maximum plasma concentration (C_max), the area under the curve of plasma concentration-time from zero to the last measurable concentration (AUC_0 - t) and the area under the curve of blood concentration from zero to infinity (AUC_0-∞) for fuzuloparib combined with efavirenz to fuzuloparib alone were 0.473 (0.394, 0.568), 0.220 (0.185, 0.263) and 0.221 (0.185, 0.263), respectively. Co-administration with efavirenz led to 53% and 78% decreases in fuzuloparib C_max and AUC_0-∞. All 18 subjects enrolled in this study were included in the safety analysis set. A total of 16 subjects had 62 AEs during the study period. No serious adverse events (SAE) were reported. Most treatment-emergent adverse events were grade 1 or 2 based on CTCAE. Only one grade 3 adverse event was observed. Concomitant intake of fuzuloparib with the moderate CYP3A inhibitor efavirenz resulted in a decrease in fuzuloparib AUC_0-∞ and C_max of 78% and 53% respectively. The results suggested that concomitant moderate CYP3A inducers should be avoided during the administration of fuzuloparib, or else the dosage adjustments should be required. (This trial was registered at http://www.chinadrugtrials.org.cn . The registration No. is CTR20211022, and the date of registration is 2021-05-13).

Guidance on the management of adverse reactions induced by poly(ADP-ribose) polymerase inhibitors

The common adverse reactions caused by poly (ADP-ribose) polymerase (PARP) inhibitors include hematological toxicity, gastrointestinal toxicity and fatigue. The main prevention and treatment of hematological toxicity include: regular blood tests, referral to hematology department when routine treatment is ineffective, and being alert of myelodysplastic syndrome/acute myeloid leukemia. The key points to deal with gastrointestinal toxicity include: taking medicine at the right time, light diet, appropriate amount of drinking water, timely symptomatic treatment, prevention of expected nausea and vomiting, and so on. For fatigue, full assessment should be completed before treatment because the causes of fatigue are various; the management includes massage therapy, psychosocial interventions and drugs such as methylphenidate and Panax quinquefolius according to the severity. In addition, niraparib and fluzoparib can cause hypertension, hypertensive crisis and palpitation. Blood pressure and heart rate monitoring, timely symptomatic treatment, and multidisciplinary consultation should be taken if necessary. When cough and dyspnea occur, high resolution CT and bronchoscopy should be performed to exclude pneumonia. If necessary, PARP inhibitors should be stopped, and glucocorticoid and antimicrobial therapy should be given. Finally, more attention should be paid to drug interaction management, patient self-management and regular monitoring to minimize the risk and harm of adverse reactions of PARP inhibitors.

Predicting transporter mediated drug-drug interactions via static and dynamic physiologically based pharmacokinetic modeling: A comprehensive insight on where we are now and the way forward

The greater utilization and acceptance of physiologically-based pharmacokinetic (PBPK) modeling to evaluate the potential metabolic drug-drug interactions is evident by the plethora of literature, guidance's, and regulatory dossiers available in the literature. In contrast, it is not widely used to predict transporter-mediated DDI (tDDI). This is attributed to the unavailability of accurate transporter tissue expression levels, the absence of accurate in vitro to in vivo extrapolations (IVIVE), enzyme-transporter interplay, and a lack of specific probe substrates. Additionally, poor understanding of the inhibition/induction mechanisms coupled with the inability to determine unbound concentrations at the interaction site made tDDI assessment challenging. Despite these challenges, continuous improvements in IVIVE approaches enabled accurate tDDI predictions. Furthermore, the necessity of extrapolating tDDI's to special (pediatrics, pregnant, geriatrics) and diseased (renal, hepatic impaired) populations is gaining impetus and is encouraged by regulatory authorities. This review aims to visit the current state-of-the-art and summarizes contemporary knowledge on tDDI predictions. The current understanding and ability of static and dynamic PBPK models to predict tDDI are portrayed in detail. Peer-reviewed transporter abundance data in special and diseased populations from recent publications were compiled, enabling direct input into modeling tools for accurate tDDI predictions. A compilation of regulatory guidance's for tDDI's assessment and success stories from regulatory submissions are presented. Future perspectives and challenges of predicting tDDI in terms of in vitro system considerations, endogenous biomarkers, the use of empirical scaling factors, enzyme-transporter interplay, and acceptance criteria for model validation to meet the regulatory expectations were discussed.

Dose Adjustment of Poly (ADP‑Ribose) Polymerase Inhibitors in Patients with Hepatic or Renal Impairment

Poly (ADP-ribose) polymerase (PARP) inhibitors are small-molecule inhibitors of PARP enzymes (including PARP1, PARP2, and PARP3) that exhibit activity against tumor cells with defects in DNA repair. In recent years, five PARP inhibitors, olaparib, niraparib, rucaparib, talazoparib and veliparib, have been developed for the treatment of solid tumors, particularly in patients with breast-related cancer antigen (BRCA) 1/2 mutations, or those without a functional homologous recombination repair pathway. These novel treatments exhibit improved efficacy and toxicity when compared to conventional chemotherapy agents. The five PARP inhibitors are eliminated primarily via the liver and kidneys, hepatic or renal impairment may significantly affect their pharmacokinetics (PK). Therefore, it is important to know the effects of hepatic or renal impairment on the PK and safety of PARP inhibitors. In this review, we characterize and summarize the effects of hepatic and renal function on the PK of PARP inhibitors and provide specific recommendations for clinicians when prescribing PARP inhibitors in patients with hepatic or renal impairment.

PARP targeted Auger emitter therapy with [125I]PARPi-01 for triple-negative breast cancer

BACKGROUND

Triple-negative breast cancer (TNBC) lacks biomarkers for targeted therapy. Auger emitters display the best therapeutic effect, if delivered directly into the nucleus proximal to DNA. The nuclear protein Poly (ADP-ribose)-Polymerase 1 (PARP1) is a suitable target against which few inhibitors (PARPi) are clinically approved for treatment of breast cancer with germline BRCA mutation (BRCA^mut). In this study, a theranostic approach was investigated in a TNBC xenografted mouse model by radiolabelling a close derivative of a PARPi Olaparib (termed PARPi-01) with the Auger emitters ^123/125I.

METHODS

TNBC cell line MDA-MB-231 was subcutaneously implanted in female NOD/SCID mice. At a tumour size of ~ 500mm³, [¹²³I]PARPi-01 was administered intravenously, and SPECT/CT images were obtained at 4 h or 24 h post injection (p.i). A therapy study was performed with [¹²⁵I]PARPi-01 in 4 doses (10 MBq/dose, 10 days apart). Tumour growth was monitored by CT scans longitudinally once per week. Upon reaching study endpoint, tissues were harvested and stained with TUNEL assay for detection of apoptosis induction.

RESULTS

SPECT/CT images showed rapid hepatobiliary tracer clearance at 4 h post injection (p.i.). Retention in thyroid at 24 h p.i. suggested tracer deiodination in vivo. The tumour and liver uptake were 0.2%ID/g and 2.5%ID/g, respectively. The tumour: blood ratio was 1.3. Endogenous therapy induced a significant delay in tumour growth (doubling time increased from 8.3 to 14.2 days), but no significant survival advantage. Significantly higher apoptosis ratio was observed in [¹²⁵I]PARPi-01 treated tumour tissues. No radiotoxicity was detected in the liver and thyroid.

CONCLUSION

Considering the radio-cytotoxic effect in the tumour tissue and a delay on tumour doubling time, [¹²⁵I]PARPi-01 presents a potential radiotherapeutics for treatment of TNBC. Improvements to overcome the suboptimal pharmacokinetics are necessary for its potential clinical application.

A Real-World Disproportionality Analysis of Olaparib: Data Mining of the Public Version of FDA Adverse Event Reporting System

Background

Olaparib, the world’s first poly ADP-ribose polymerase (PARP) inhibitor (PARPi), has been approved for treatment of ovarian cancer, breast cancer, pancreatic cancer and prostate cancer by FDA. The current study was to assess olaparib-related adverse events (AEs) of real-world through data mining of the US Food and Drug Administration Adverse Event Reporting System (FAERS).

Methods

Disproportionality analyses, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN) and the multi-item gamma Poisson shrinker (MGPS) algorithms were employed to quantify the signals of olaparib-associated AEs.

Results

Out of 8,450,009 reports collected from the FAERS database, 6402 reports of olaparib-associated AEs were identified. A total of 118 significant disproportionality preferred terms (PTs) conforming to the four algorithms simultaneously were retained. The most common AEs included anemia, thrombocytopenia, nausea, decreased appetite, blood creatinine increased and dermatomyositis, which were corresponding to those reported in the specification and clinical trials. Unexpected significant AEs as interstitial lung disease, Pneumocystis jirovecii pneumonia, folate deficiency, renal impairment and intestinal obstruction might also occur. The median onset time of olaparib-related AEs was 61 days (interquartile range [IQR] 14–182 days), and most of the cases occurred within the first 1 month after olaparib initiation.

Conclusion

Results of our study were consistent with clinical observations, and we also found potential new and unexpected AEs signals for olaparib, suggesting prospective clinical studies were needed to confirm these results and illustrate their relationship. Our results could provide valuable evidence for further safety studies of olaparib.

Multi-Disciplinary Care Planning of Ovarian Cancer in Older Patients: General Statement-A Position Paper from SOFOG-GINECO-FRANCOGYN-SFPO

Simple Summary

This position paper aims to provide practitioners a proposal for multidisciplinary care planning for older patients with ovarian cancer from the time of suspected diagnosis. The first-line treatment of advanced ovarian cancer involves several interdependent sequences: cytoreductive surgery, (neo)adjuvant chemotherapy and maintenance targeted treatments. In older patients, care planning must be adapted to their geriatric parameters and consider the geriatric impact of each treatment sequence to allow treatment completion. Care planning should be centered on patient motivation and imply multidisciplinarity. Each step of treatment plan should be reconsidered in light of a geriatric assessment and follow-up. Studies are needed to prospectively evaluate the impact of geriatric vulnerability parameters at each step of the treatment agenda and the impact of geriatric interventions on patient outcomes.

Abstract

In this position paper the Société Francophone d’OncoGériatrie (SOFOG; French-speaking oncogeriatric society), the Société Française de Pharmacie Oncologique (SFPO, French society for oncology pharmacy), the Groupe d’Investigateurs Nationaux pour l’Étude des Cancers de l’Ovaire et du sein (GINECO, National Investigators’ Group for Studies in Ovarian and Breast Cancer) and the Groupe Français de chirurgie Oncologique et Gynécologique (FRANCOGYN) propose a multi-disciplinary care planning of ovarian cancer in older patients. The treatment pathway is based on four successive decisional nodes (diagnosis, resectability assessment, operability assessment, adjuvant, and maintenance treatment decision) implying multidisciplinarity and adaptation of the treatment plan according to the patient’s geriatric covariates and her motivation towards treatment. Specific attention must be paid to geriatric intervention, supportive care and pharmaceutical conciliation. Studies are needed to prospectively evaluate the impact of geriatric vulnerability parameters at each step of the treatment agenda and the impact of geriatric interventions on patient outcomes.

Pharmacokinetics and Pharmacodynamics of PARP Inhibitors in Oncology

Olaparib, niraparib, rucaparib, and talazoparib are poly (ADP-ribose) polymerase (PARP) inhibitors approved for the treatment of ovarian, breast, pancreatic, and/or prostate cancer. Poly (ADP-ribose) polymerase inhibitors are potent inhibitors of the PARP enzymes with comparable half-maximal inhibitory concentrations in the nanomolar range. Olaparib and rucaparib are orally dosed twice a day, extensively metabolized by cytochrome P450 enzymes, and inhibitors of several enzymes and drug transporters with a high risk for drug-drug interactions. Niraparib and talazoparib are orally dosed once a day with a lower risk for niraparib and a minimal risk for talazoparib to cause drug-drug interactions. All four PARP inhibitors show moderate-to-high interindividual variability in plasma exposure. Higher exposure is associated with an increase in toxicity, mostly hematological toxicity. For talazoparib, exposure-efficacy relationships have been described, but for olaparib, niraparib, and rucaparib this relationship remains inconclusive. Further studies are required to investigate exposure-response relationships to improve dosing of PARP inhibitors, in which therapeutic drug monitoring could play an important role. In this review, we give an overview of the pharmacokinetic properties of the four PARP inhibitors, including considerations for patients with renal dysfunction or hepatic impairment, the effect of food, and drug-drug interactions. Furthermore, we focus on the pharmacodynamics and summarize the available exposure-efficacy and exposure-toxicity relationships.

Effect of fluconazole on the pharmacokinetics of fuzuloparib: an open-label, crossover study in Chinese healthy male volunteers

PURPOSE

Fuzuloparib (AiRuiYiTM, formerly fluzoparib, SHR3162) is a new orally active poly adenosine diphosphate ribose polymerase (PARP) inhibitor. It has multiple pharmacological activities in breast, ovarian, and prostatic cancer. Fuzuloparib is mainly metabolized through the enzyme CYP3A4 may slow fuzuloparib metabolism and increase its concentrations in blood. We evaluated the pharmacokinetics and tolerability of fuzuloparib by fluconazole, which is a broad antifungal agent and a moderate inhibitor of CYP3A4.

METHODS

In this study, the effects of CYP3A4 inhibition on the pharmacokinetics of fuzuloparib were assessed in a total of 20 healthy Chinese male subjects in an open-label, two-period, single-sequence, crossover study.

RESULTS

Pharmacokinetic parameters, including the maximal plasma concentration (Cmax), the plasma concentration-time curve from time 0 to last measurable area under concentration (AUC0-t), and from time 0 to infinity (AUC0-∞), were increased by 32.4%, 104.5%, and 109.6%, with corresponding 90% confidence intervals of (23-43%), (93-116%), and (98-122%), respectively, when fluconazole was combined with fuzuloparib compared to fuzuloparib alone. There was also a slight increase in the incidence of treatment emergent adverse events, including hyperlipidemia and elevated aspartate transaminase.

CONCLUSION

The fuzuloparib is 150 mg b.i.d in clinics use. Our results suggest that fuzuloparib could well be tolerated when administered as a single 20 mg oral dose alone or co-administered with 400 mg fluconazole in healthy male subjects. It is recommended to avoid using moderate CYP3A4 inhibitors together with fuzuloparib or instead of 50 mg when necessary.

Metabolism‑related pharmacokinetic drug‑drug interactions with poly (ADP‑ribose) polymerase inhibitors (Review)

Poly (ADP‑ribose) polymerase (PARP) inhibitors, including olaparib, niraparib, rucaparib, talazoparib and veliparib, have emerged as one of the most exciting new treatments for solid tumors, particularly in patients with breast‑related cancer antigen 1/2 mutations. Oral administration is convenient and shows favorable compliance with the majority of patients, but it may be affected by numerous factors, including food, metabolic enzymes and transporters. These interactions may be associated with serious adverse drug reactions or may reduce the treatment efficacy of PARP inhibitors. In fact, numerous pharmacokinetic (PK)‑based drug‑drug interactions (DDIs) involve the metabolism of PARP inhibitors, particularly those metabolized via cytochrome P450 enzymes. The present review aims to characterize and summarize the metabolism‑related PK‑based DDIs of PARP inhibitors, and to provide specific recommendations for reducing the risk of clinically significant DDIs.

Unraveling pleiotropic effects of rifampicin by using physiologically based pharmacokinetic modeling: Assessing the induction magnitude of P-glycoprotein-cytochrome P450 3A4 dual substrates

Rifampicin induces both P-glycoprotein (P-gp) and cytochrome P450 3A4 (CYP3A4) through regulating common nuclear receptors (e.g., pregnane X receptor). The interplay of P-gp and CYP3A4 has emerged to be an important factor in clinical drug-drug interactions (DDIs) with P-gp-CYP3A4 dual substrates and requires qualitative and quantitative understanding. Although physiologically based pharmacokinetic (PBPK) modeling has become a widely accepted approach to assess DDIs and is able to reasonably predict DDIs caused by CYP3A4 induction and P-gp induction individually, the predictability of PBPK models for the effect of simultaneous P-gp and CYP3A4 induction on P-gp-CYP3A4 dual substrates remains to be systematically evaluated. In this study, we used a PBPK modeling approach for the assessment of DDIs between rifampicin and 12 drugs: three sensitive P-gp substrates, seven P-gp-CYP3A4 dual substrates, and two P-gp-CYP3A4 dual substrates and inhibitors. A 3.5-fold increase of intestinal P-gp abundance was incorporated in the PBPK models to account for rifampicin-mediated P-gp induction at steady state. The simulation results showed that accounting for P-gp induction in addition to CYP3A4 induction improved the prediction accuracy of the area under the concentration-time curve and maximum (peak) plasma drug concentration ratios compared with considering CYP3A4 induction alone. Furthermore, the interplay of relevant drug-specific parameters and its impact on the magnitude of DDIs were evaluated using sensitivity analysis. The PBPK approach described herein, in conjunction with robust in vitro and clinical data, can help in the prospective assessment of DDIs involving other P-gp and CYP3A4 dual substrates. The database reported in the present study provides a valuable aid in understanding the combined effect of P-gp and CYP3A4 induction during drug development.

A Review of CYP3A Drug-Drug Interaction Studies: Practical Guidelines for Patients Using Targeted Oral Anticancer Drugs

Many oral anticancer drugs are metabolized by CYP3A. Clinical drug-drug interaction (DDI) studies often only examine the effect of strong CYP3A inhibitors and inducers. The effect of moderate or weak inhibitors or inducers can be examined using physiologically based pharmacokinetic simulations, but data from these simulations are not always available early after approval of a drug. In this review we provide recommendations for clinical practice on how to deal with DDIs of oral anticancer drugs if only data from strong CYP3A inhibitors or inducers is available. These recommendations were based on reviewed data of oral anticancer drugs primarily metabolized by CYP3A and approved for the treatment of solid tumors from January 1st, 2013 to December 31st, 2015. In addition, three drugs that were registered before the new EMA guideline was issued (i.e., everolimus, imatinib, and sunitinib), were reviewed. DDIs are often complex, but if no data is available from moderate CYP3A inhibitors/inducers, a change in exposure of 50% compared with strong inhibitors/inducers can be assumed. No a priori dose adaptations are indicated for weak inhibitors/inducers, because their interacting effect is small. In case pharmacologically active metabolites are involved, the metabolic pathway, the ratio of the parent to the metabolites, and the potency of the metabolites should be taken into account.

Physiologically-Based Pharmacokinetic Modelling of Entrectinib Parent and Active Metabolite to Support Regulatory Decision-Making

BACKGROUND AND OBJECTIVE

Entrectinib is a selective inhibitor of ROS1/TRK/ALK kinases, recently approved for oncology indications. Entrectinib is predominantly cleared by cytochrome P450 (CYP) 3A4, and modulation of CYP3A enzyme activity profoundly alters the pharmacokinetics of both entrectinib and its active metabolite M5. We describe development of a combined physiologically based pharmacokinetic (PBPK) model for entrectinib and M5 to support dosing recommendations when entrectinib is co-administered with CYP3A4 inhibitors or inducers.

METHODS

A PBPK model was established in Simcyp^® Simulator. The initial model based on in vitro-in vivo extrapolation was refined using sensitivity analysis and non-linear mixed effects modeling to optimize parameter estimates and to improve model fit to data from a clinical drug-drug interaction study with the strong CYP3A4 inhibitor, itraconazole. The model was subsequently qualified against clinical data, and the final qualified model used to simulate the effects of moderate to strong CYP3A4 inhibitors and inducers on entrectinib and M5 pharmacokinetics.

RESULTS

The final model showed good predictive performance for entrectinib and M5, meeting commonly used predictive performance acceptance criteria in each case. The model predicted that co-administration of various moderate CYP3A4 inhibitors (verapamil, erythromycin, clarithromycin, fluconazole, and diltiazem) would result in an average increase in entrectinib exposure between 2.2- and 3.1-fold, with corresponding average increases for M5 of approximately 2-fold. Co-administration of moderate CYP3A4 inducers (efavirenz, carbamazepine, phenytoin) was predicted to result in an average decrease in entrectinib exposure between 45 and 79%, with corresponding average decreases for M5 of approximately 50%.

CONCLUSIONS

The model simulations were used to derive dosing recommendations for co-administering entrectinib with CYP3A4 inhibitors or inducers. PBPK modeling has been used in lieu of clinical studies to enable regulatory decision-making.

Association between Olaparib Exposure and Early Toxicity in BRCA-Mutated Ovarian Cancer Patients: Results from a Retrospective Multicenter Study

Factors associated with olaparib toxicity remain unknown in ovarian cancer patients. The large inter-individual variability in olaparib pharmacokinetics could contribute to the onset of early significant adverse events (SAE). We aimed to retrospectively analyze the pharmacokinetic/pharmacodynamic relationship for toxicity in ovarian cancer patients from “real life” data. The clinical endpoint was the onset of SAE (grade III/IV toxicity or dose reduction/discontinuation). Plasma olaparib concentration was assayed using liquid chromatography at any time over the dosing interval. Trough concentrations (CminPred) were estimated using a population pharmacokinetic model. The association between toxicity and clinical characteristics or CminPred was assessed by logistic regression and non-parametric statistical tests. Twenty-seven patients were included, among whom 13 (48%) experienced SAE during the first six months of treatment. Olaparib CminPred was the only covariate significantly associated with increased risk of SAE onset (odds ratio = 1.31, 95% CI = [1.10; 1.57], for each additional 1000 ng/mL). The ROC curve identified a threshold of CminPred = 2500 ng/mL for prediction of SAE onset (sensitivity/specificity 0.62 and 1.00, respectively). This study highlights a significant association between olaparib plasma exposure and SAE onset and identified the threshold of 2500 ng/mL trough concentration as potentially useful to guide dose adjustment in ovarian cancer patients.

Overview of Olaparib as a treatment option for metastatic castration-resistant prostate cancer

Introduction: Men with prostate cancer undergoing castration will eventually progress. In addition to androgen receptor pathway inhibitors (like abiraterone and enzalutamide) or chemotherapy (like docetaxel), exists olaparib, a relatively new drug that interferes with the base excision repair (BER) pathway mainly due to selective inhibition of Poly ADP-ribose polymerase (PARP) 1 and 2.Areas covered: Herein, the authors evaluate the basic characteristics of olaparib, including its pharmacokinetics, mechanism of action, efficacy, and safety profile. The authors also provide their expert opinion and future perspectives for the place of this drug in the current treatment armamentarium.Expert opinion: Olaparib is the first drug to prove that genetic sequencing and precise medicine is a viable and important option for prostate cancer patients. In patients with deletions in preselected genes, its efficacy renders it as a viable option for second- or third-line management of metastatic castrate resistance prostate cancer (mCRPC). This fact, along with its acceptable toxicity profile, provide physicians with a new weapon in their armamentarium against this extremely difficult to treat disease.

A review of the evidence base for utilizing Child-Pugh criteria for guiding dosing of anticancer drugs in patients with cancer and liver impairment

As the liver is vital for the metabolism of many anticancer drugs, determining the correct starting doses in cancer patients with liver impairment is key to safe prescription and prevention of unnecessary adverse effects. Clinicians typically use liver function tests when evaluating patients; however, prescribing information and summaries of product characteristics often suggest dosing of anticancer drugs in patients with liver impairment based on the Child-Pugh criteria, even though the criteria were not developed for this purpose. In this review, we assessed all the oncological small molecule and cytotoxic drugs approved by the United States Food and Drug Administration (FDA) over a 5-year period from 2014 to 2018. The various entry criteria related to these drugs—with respect to hepatic function—in key pivotal studies were compared with their approved dosing recommendations found in prescribing information and summaries of product characteristics. We found that 46% of drugs have dosing recommendations based on Child-Pugh criteria alone, despite the fact that only 8% of these drugs were tested within studies that used the Child-Pugh criteria as entry criteria. Moreover, we note that the data used to make recommendations based on Child-Pugh criteria are typically from small studies that may lack an appropriate patient population. We propose that these findings, along with details surrounding the development of the Child-Pugh criteria, call into question the validity and appropriateness of using Child-Pugh criteria for dosing recommendations of anticancer drugs.

•

Dosing information for anticancer drugs in patients with liver impairment is often based on the Child-Pugh criteria.

•

Clinical trials and clinicians typically use liver function tests when evaluating patients.

•

Of the 39 oncologic drugs examined, almost half (46%) had dosing recommendations based on Child-Pugh criteria alone.

•

We question whether using Child-Pugh criteria for dosing recommendations of anticancer drugs is the best approach.

Current challenges and future perspectives in oral absorption research: An opinion of the UNGAP network

Although oral drug delivery is the preferred administration route and has been used for centuries, modern drug discovery and development pipelines challenge conventional formulation approaches and highlight the insufficient mechanistic understanding of processes critical to oral drug absorption. This review presents the opinion of UNGAP scientists on four key themes across the oral absorption landscape: (1) specific patient populations, (2) regional differences in the gastrointestinal tract, (3) advanced formulations and (4) food-drug interactions. The differences of oral absorption in pediatric and geriatric populations, the specific issues in colonic absorption, the formulation approaches for poorly water-soluble (small molecules) and poorly permeable (peptides, RNA etc.) drugs, as well as the vast realm of food effects, are some of the topics discussed in detail. The identified controversies and gaps in the current understanding of gastrointestinal absorption-related processes are used to create a roadmap for the future of oral drug absorption research.

Food constituent- and herb-drug interactions in oncology: Influence of quantitative modelling on Drug labelling

AIMS

Herbal products, spices and/or fruits are perceived as inherently healthy; for instance, St. John's wort (SJW) is marketed as a natural antidepressant and patients often self-administer it concomitantly with oncology medications. However, food constituents/herbs can interfere with drug pharmacokinetics, with risk of altering pharmacodynamics and efficacy. The objective of this work was to develop a strategy to prioritize herb- or food constituent-drug interactions (FC-DIs) to better assess oncology drug clinical risk.

METHODS

Physiologically based pharmacokinetic (PBPK) models were developed by integrating in vitro parameters with the clinical pharmacokinetics of food constituents in grapefruit juice (bergamottin), turmeric (curcumin) or SJW (hyperforin). Perpetrator files were linked to verified victim PBPK models through appropriate interaction mechanisms (cytochrome P450 3A, breast cancer resistance protein, P-glycoprotein) and applied in prospective PBPK simulations to inform the likelihood and magnitude of changes in exposure to osimertinib, olaparib or acalabrutinib.

RESULTS

Reported FC-DIs with oncology drugs were well recovered, with absolute average fold error values of 1.10 (bergamottin), 1.05 (curcumin) and 1.01 (hyperforin). Prospective simulations with grapefruit juice and turmeric showed clinically minor to insignificant changes in exposure (<1.50-fold) to acalabrutinib, osimertinib and olaparib, but predicted 1.57-fold FC-DI risk between acalabrutinib and curcumin. Moderate DDI risk was expected when acalabrutinib, osimertinib or olaparib were dosed with SJW.

CONCLUSIONS

A model-informed decision tree based on mechanistic understanding of transporter and/or enzyme-mediated FC-DI is proposed based on bergamottin, curcumin and hyperforin FC-DI clinical data. Adopting this quantitative modelling approach should streamline herbal product safety assessments, assist in FC-DI management, and ultimately promote safe clinical use of oncology drugs.

Pharmacokinetics under the COVID-19 storm

AIMS

The storm-like nature of the health crises caused by COVID-19 has led to unconventional clinical trial practices such as the relaxation of exclusion criteria. The question remains: how can we conduct diverse trials without exposing subgroups of populations to potentially harmful drug exposure levels? The aim of this study was to build a knowledge base of the effect of intrinsic/extrinsic factors on the disposition of several repurposed COVID-19 drugs.

METHODS

Physiologically based pharmacokinetic (PBPK) models were used to study the change in the pharmacokinetics (PK) of drugs repurposed for COVID-19 in geriatric patients, different race groups, organ impairment and drug-drug interactions (DDIs) risks. These models were also used to predict epithelial lining fluid (ELF) exposure, which is relevant for COVID-19 patients under elevated cytokine levels.

RESULTS

The simulated PK profiles suggest no dose adjustments are required based on age and race for COVID-19 drugs, but dose adjustments may be warranted for COVID-19 patients also exhibiting hepatic/renal impairment. PBPK model simulations suggest ELF exposure to attain a target concentration was adequate for most drugs, except for hydroxychloroquine, azithromycin, atazanavir and lopinavir/ritonavir.

CONCLUSION

We demonstrate that systematically collated data on absorption, distribution, metabolism and excretion, human PK parameters, DDIs and organ impairment can be used to verify simulated plasma and lung tissue exposure for drugs repurposed for COVID-19, justifying broader patient recruitment criteria. In addition, the PBPK model developed was used to study the effect of age and ethnicity on the PK of repurposed drugs, and to assess the correlation between lung exposure and relevant potency values from in vitro studies for SARS-CoV-2.

Model-Informed Pediatric Dose Selection for Dapagliflozin by Incorporating Developmental Changes

This analysis reports a quantitative modeling and simulation approach for oral dapagliflozin, a primarily uridine diphosphate-glucuronosyltransferase (UGT)-metabolized human sodium-glucose cotransporter 2 selective inhibitor. A mechanistic dapagliflozin physiologically based pharmacokinetic (PBPK) model was developed using in vitro metabolism and clinical pharmacokinetic (PK) data and verified for context of use (e.g., exposure predictions in pediatric subjects aged 1 month to 18 years). Dapagliflozin exposure is challenging to predict in pediatric populations owing to differences in UGT1A9 ontogeny maturation and paucity of clinical PK data in younger age groups. Based on the exposure-response relationship of dapagliflozin, twofold acceptance criteria were applied between model-predicted and observed drug exposures and PK parameters (area under the curve and maximum drug concentration) in various scenarios, including monotherapy in healthy adults (single/multiple dose), monotherapy in hepatically or renally impaired patients, and drug-drug interactions with UGT1A9 modulators, such as mefenamic acid and rifampin. The PBPK model captured the observed exposure within twofold of the observed monotherapy data in adults and adolescents and in special population. As a guide to determining dosing regimens in pediatric studies, the verified PBPK model, along with UGT enzyme ontogeny maturation understanding, was used for predictions of dapagliflozin monotherapy exposures in pediatric subjects aged 1 month to 18 years that best matched exposure in adult patients with a 10-mg single dose of dapagliflozin.

A GFR-Based Method to Predict the Effect of Renal Impairment on the Exposure or Clearance of Renally Excreted Drugs: A Comparative Study Between a Simple GFR Method and a Physiologically Based Pharmacokinetic Model

Objective

The objective of this study was to compare the predictive performances of a glomerular filtration rate (GFR) model with a physiologically based pharmacokinetic (PBPK) model to predict total or renal clearance or area under the curve of renally excreted drugs in subjects with varying degrees of renal impairment.

Methods

From the literature, 11 studies were randomly selected in which total or renal clearance or area under the curve of drugs in subjects with different degrees of renal impairment were predicted by PBPK models. In these published studies, drugs were given to subjects intravenously or orally. The PBPK model was generally a whole-body model whereas the GFR model was as follows: Predicted total clearance (CL_T) = CL_T in healthy subjects × (GFR in RI/GFR in H), Predicted AUC = AUC in healthy subjects × (GFR in H/GFR in RI), where H is the healthy subjects and RI is renal impairment. The predicted clearance or area under the curve values using PBPK and GFR models were compared with the observed (experimental pharmacokinetic) values. The acceptable prediction error was within the 0.5- to 2-fold or 0.5- to 1.5-fold prediction error.

Results

There were 33 drugs with a total number of 101 observations (area under the curve, total and renal clearance in subjects with mild, moderate, and severe renal impairment). From PBPK and GFR models, out of 101 observations, 94 (93.1%) and 96 (95.0%) observations were within the 0.5- to 2-fold prediction error, respectively.

Conclusions

This study indicates that the predictive power of a simple GFR model is similar to a PBPK model for the prediction of clearance or area under the curve in subjects with renal impairment. The GFR method is simple, robust, and reliable and can replace complex empirical PBPK models.

Quantitative Assessment of Elagolix Enzyme-Transporter Interplay and Drug-Drug Interactions Using Physiologically Based Pharmacokinetic Modeling

INTRODUCTION

Elagolix is approved for the management of moderate-to-severe pain associated with endometriosis. The aim of this analysis was to develop a physiologically based pharmacokinetic (PBPK) model that describes the enzyme-transporter interplay involved in the disposition of elagolix and to predict the magnitude of drug-drug interaction (DDI) potential of elagolix as an inhibitor of P-glycoprotein (P-gp) and inducer of cytochrome P450 (CYP) 3A4.

METHODS

A PBPK model (SimCYP® version 15.0.86.0) was developed using elagolix data from in vitro, clinical PK and DDI studies. Data from DDI studies were used to quantify contributions of the uptake transporter organic anion transporting polypeptide (OATP) 1B1 and CYP3A4 in the disposition of elagolix, and to quantitatively assess the perpetrator potential of elagolix as a CYP3A4 inducer and P-gp inhibitor.

RESULTS

After accounting for the interplay between elagolix metabolism by CYP3A4 and uptake by OATP1B1, the model-predicted PK parameters of elagolix along with the DDI AUC∞ and Cmax ratios, were within 1.5-fold of the observed data. Based on model simulations, elagolix 200 mg administered twice daily is a moderate inducer of CYP3A4 (approximately 56% reduction in midazolam AUC∞). Simulations of elagolix 150 mg administered once daily with digoxin predicted an increase in digoxin Cmax and AUC∞ by 68% and 19%, respectively.

CONCLUSIONS

A PBPK model of elagolix was developed, verified, and applied to characterize the disposition interplay between CYP3A4 and OATP1B1, and to predict the DDI potential of elagolix as a perpetrator under dosing conditions that were not tested clinically. PBPK model-based predictions were used to support labeling language for DDI recommendations of elagolix.

Pharmacokinetics and safety of olaparib in patients with advanced solid tumours and mild or moderate hepatic impairment

AIMS

Olaparib, a potent oral poly(ADP-ribose) polymerase inhibitor, is partially hepatically cleared. We investigated the pharmacokinetics (PK) and safety of olaparib in patients with mild or moderate hepatic impairment to provide dosing recommendations.

METHODS

This Phase I open-label study assessed the PK, safety and tolerability of single doses of olaparib 300-mg tablets in patients with advanced solid tumours. Patients had normal hepatic function (NHF), or mild (MiHI; Child-Pugh class A) or moderate (MoHI; Child-Pugh class B) hepatic impairment. Blood was collected for PK assessments for 96 hours. Patients could continue taking olaparib 300 mg twice daily for long-term safety assessment.

RESULTS

Thirty-one patients received ≥1 dose of olaparib and 30 were included in the PK assessment. Patients with MiHI had an area under the curve geometric least-squares mean (GLSmean) ratio of 1.15 (90% confidence interval 0.72, 1.83) and a GLSmean maximum plasma concentration ratio of 1.13 (0.82, 1.56) vs those with NHF. In patients with MoHI, GLSmean ratio for area under the curve was 1.08 (0.66, 1.74) and for maximum plasma concentration was 0.87 (0.63, 1.22) vs those with NHF. For patients with mild or moderate hepatic impairment, no new safety signals were detected.

CONCLUSION

Patients with MiHI or MoHI had no clinically significant changes in exposure to olaparib compared with patients with NHF. The safety profile of olaparib did not differ from a clinically relevant extent between cohorts. No olaparib tablet or capsule dose reductions are required for patients with MiHI or MoHI.

Further Considerations Towards an Effective and Efficient Oncology Drug Discovery DMPK Strategy

BACKGROUND

DMPK data and knowledge are critical in maximising the probability of developing successful drugs via the application of in silico, in vitro and in vivo approaches in drug discovery.

METHODS

The evaluation, optimisation and prediction of human pharmacokinetics is now a mainstay within drug discovery. These elements are at the heart of the 'right tissue' component of AstraZeneca's '5Rs framework' which, since its adoption, has resulted in increased success of Phase III clinical trials. With the plethora of DMPK related assays and models available, there is a need to continually refine and improve the effectiveness and efficiency of approaches best to facilitate the progression of quality compounds for human clinical testing.

RESULTS

This article builds on previously published strategies from our laboratories, highlighting recent discoveries and successes, that brings our AstraZeneca Oncology DMPK strategy up to date. We review the core aspects of DMPK in Oncology drug discovery and highlight data recently generated in our laboratories that have influenced our screening cascade and experimental design. We present data and our experiences of employing cassette animal PK, as well as re-evaluating in vitro assay design for metabolic stability assessments and expanding our use of freshly excised animal and human tissue to best inform first time in human dosing and dose escalation studies.

CONCLUSION

Application of our updated drug-drug interaction and central nervous system drug exposure strategies are exemplified, as is the impact of physiologically based pharmacokinetic and pharmacokinetic-pharmacodynamic modelling for human predictions.

Physiologically-Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug-Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations

Physiologically-based pharmacokinetic (PBPK) modeling has been extensively used to quantitatively translate in vitro data and evaluate temporal effects from drug-drug interactions (DDIs), arising due to reversible enzyme and transporter inhibition, irreversible time-dependent inhibition, enzyme induction, and/or suppression. PBPK modeling has now gained reasonable acceptance with the regulatory authorities for the cytochrome-P450-mediated DDIs and is routinely used. However, the application of PBPK for transporter-mediated DDIs (tDDI) in drug development is relatively uncommon. Because the predictive performance of PBPK models for tDDI is not well established, here, we represent and discuss examples of PBPK analyses included in regulatory submission (the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the Pharmaceuticals and Medical Devices Agency (PMDA)) across various tDDIs. The goal of this collaborative effort (involving scientists representing 17 pharmaceutical companies in the Consortium and from academia) is to reflect on the use of current databases and models to address tDDIs. This challenges the common perceptions on applications of PBPK for tDDIs and further delves into the requirements to improve such PBPK predictions. This review provides a reflection on the current trends in PBPK modeling for tDDIs and provides a framework to promote continuous use, verification, and improvement in industrialization of the transporter PBPK modeling.

Evaluation of the Drug-Drug Interaction Potential of Acalabrutinib and Its Active Metabolite, ACP-5862, Using a Physiologically-Based Pharmacokinetic Modeling Approach

Acalabrutinib, a selective, covalent Bruton tyrosine kinase inhibitor, is a CYP3A substrate and weak CYP3A/CYP2C8 inhibitor. A physiologically‐based pharmacokinetic (PBPK) model was developed for acalabrutinib and its active metabolite ACP‐5862 to predict potential drug–drug interactions (DDIs). The model indicated acalabrutinib would not perpetrate a CYP2C8 or CYP3A DDI with the sensitive CYP substrates rosiglitazone or midazolam, respectively. The model reasonably predicted clinically observed acalabrutinib DDI with the CYP3A perpetrators itraconazole (4.80‐fold vs. 5.21‐fold observed) and rifampicin (0.21‐fold vs. 0.23‐fold observed). An increase of two to threefold acalabrutinib area under the curve was predicted for coadministration with moderate CYP3A inhibitors. When both the parent drug and active metabolite (total active components) were considered, the magnitude of the CYP3A DDI was much less significant. PBPK dosing recommendations for DDIs should consider the magnitude of the parent drug excursion, relative to safe parent drug exposures, along with the excursion of total active components to best enable safe and adequate pharmacodynamic coverage.

Pharmacokinetics and safety of olaparib tablets as monotherapy and in combination with paclitaxel: results of a Phase I study in Chinese patients with advanced solid tumours

PURPOSE

Chinese patients have been enrolled in multiple Phase III trials of the poly(ADP-ribose) polymerase (PARP) inhibitor olaparib (Lynparza); however, the pharmacokinetic (PK) profile of olaparib has not been investigated in this population. This two-part, open-label Phase I study was, therefore, carried out to determine the PK and safety profile of olaparib (tablet formulation) in Chinese patients with advanced solid tumours as monotherapy and in combination with paclitaxel (NCT02430311).

METHODS

The PK profile of olaparib 300 mg (twice daily [bid]; Cohort 1) as monotherapy after a single dose and at steady state, and 100 mg (bid; Cohort 2) as monotherapy (single dose and at steady state) and in combination (at steady state) with weekly paclitaxel (80 mg/m²) was assessed during Part A. Patients could continue to receive treatment (monotherapy, Cohort 1; combination therapy, Cohort 2) in Part B, which assessed safety and tolerability.

RESULTS

Twenty and 16 patients were enrolled into Cohorts 1 and 2, respectively. Steady-state olaparib exposure increased slightly less than proportionally with increasing monotherapy dose and inter-patient variability was high. A statistically significant decrease in olaparib exposure was seen when given in combination with paclitaxel. Discontinuation due to adverse events (AEs) was rare and haematological AEs were more common in patients receiving combination treatment.

CONCLUSIONS

The PK and safety profile of olaparib monotherapy in Chinese patients is consistent with that seen previously in Western and Japanese patients, and the recommended Phase III monotherapy tablet dose (300 mg bid) is suitable for use in this population.