Virtual twins for model-informed precision dosing of clozapine in patients with treatment-resistant schizophrenia

Model-informed precision dosing using virtual twins (MIPD-VTs) is an emerging strategy to predict target drug concentrations in clinical practice. Using a high virtualization MIPD-VT approach (Simcyp version 21), we predicted the steady-state clozapine concentration and clozapine dosage range to achieve a target concentration of 350 to 600 ng/mL in hospitalized patients with treatment-resistant schizophrenia (N = 11). We confirmed that high virtualization MIPD-VT can reasonably predict clozapine concentrations in individual patients with a coefficient of determination (R2 ) ranging between 0.29 and 0.60. Importantly, our approach predicted the final dosage range to achieve the desired target clozapine concentrations in 73% of patients. In two thirds of patients treated with fluvoxamine augmentation, steady-state clozapine concentrations were overpredicted two to four-fold. This work supports the application of a high virtualization MIPD-VT approach to inform the titration of clozapine doses in clinical practice. However, refinement is required to improve the prediction of pharmacokinetic drug-drug interactions, particularly with fluvoxamine augmentation.

Pharmacogenomics - a minor rather than major force in clinical medicine

INTRODUCTION

Pharmacogenomics (PGx) is touted as essential for the future of precision medicine. But the opportunity cost of PGx from the prescribers' perspective is rarely considered. The aim of this article is to critique PGx-guided prescribing using clinical pharmacology principles so that important cases for PGx testing are not missed by doctors responsible for therapeutic decision making.

AREAS COVERED

Three categories of PGx and their limitations are outlined - exposure PGx, response PGx, and immune-mediated safety PGx. Clinical pharmacology reasons are given for the narrow scope of PGx-guided prescribing apart from a few medical specialties. Clinical problems for doctors that may arise from PGx are then explained, including mismatch between patients' expectations of PGx testing and the benefits or answers it provides.

EXPERT OPINION

Contrary to popular opinion, PGx is unlikely to become the cornerstone of precision medicine. Sound clinical pharmacology reasons explain why PGx-guided prescribing is unnecessary for most drugs. Pharmacogenomics is important for niche areas of prescribing but has limited clinical utility more broadly. The opportunity cost of PGx-guided prescribing is currently too great for most doctors.

A phase I trial of SON-1010, a tumor-targeted, interleukin-12-linked, albumin-binding cytokine, shows favorable pharmacokinetics, pharmacodynamics, and safety in healthy volunteers

Background

The benefits of recombinant interleukin-12 (rIL-12) as a multifunctional cytokine and potential immunotherapy for cancer have been sought for decades based on its efficacy in multiple mouse models. Unexpected toxicity in the first phase 2 study required careful attention to revised dosing strategies. Despite some signs of efficacy since then, most rIL-12 clinical trials have encountered hurdles such as short terminal elimination half-life (T½), limited tumor microenvironment targeting, and substantial systemic toxicity. We developed a strategy to extend the rIL-12 T½ that depends on binding albumin in vivo to target tumor tissue, using single-chain rIL-12 linked to a fully human albumin binding (FHAB) domain (SON-1010). After initiating a dose-escalation trial in patients with cancer (SB101), a randomized, double-blind, placebo-controlled, single-ascending dose (SAD) phase 1 trial in healthy volunteers (SB102) was conducted.

Methods

SB102 (NCT05408572) focused on safety, tolerability, pharmacokinetic (PK), and pharmacodynamic (PD) endpoints. SON-1010 at 50-300 ng/kg or placebo administered subcutaneously on day 1 was studied at a ratio of 6:2, starting with two sentinels; participants were followed through day 29. Safety was reviewed after day 22, before enrolling the next cohort. A non-compartmental analysis of PK was performed and correlations with the PD results were explored, along with a comparison of the SON-1010 PK profile in SB101.

Results

Participants receiving SON-1010 at 100 ng/kg or higher tolerated the injection but generally experienced more treatment-emergent adverse effects (TEAEs) than those receiving the lowest dose. All TEAEs were transient and no other dose relationship was noted. As expected with rIL-12, initial decreases in neutrophils and lymphocytes returned to baseline by days 9-11. PK analysis showed two-compartment elimination in SB102 with mean T½ of 104 h, compared with one-compartment elimination in SB101, which correlated with prolonged but controlled and dose-related increases in interferon-gamma (IFNγ). There was no evidence of cytokine release syndrome based on minimal participant symptoms and responses observed with other cytokines.

Conclusion

SON-1010, a novel presentation for rIL-12, was safe and well-tolerated in healthy volunteers up to 300 ng/kg. Its extended half-life leads to a prolonged but controlled IFNγ response, which may be important for tumor control in patients.

Clinical trial registration

https://clinicaltrials.gov/study/NCT05408572, identifier NCT05408572.

Beyond Population-Level Targets for Drug Concentrations: Precision Dosing Needs Individual-Level Targets that Include Superior Biomarkers of Drug Responses

The purpose of precision dosing is to increase the chances of therapeutic success in individual patients. This is achieved in practice by adjusting doses to reach precision dosing targets determined previously in relevant populations, ideally with robust supportive evidence showing improved clinical outcomes compared with standard dosing. But is this implicit assumption of translatable population-level precision dosing targets correct and the best for all patients? In this review, the types of precision dosing targets and how they are determined are outlined, problems with the translatability of these targets to individual patients are identified, and ways forward to address these challengers are proposed. Achieving improved clinical outcomes to support precision dosing over standard dosing is currently hampered by applying population-level targets to all patients. Just as "one-dose-fits-all" may be an inappropriate philosophy for drug treatment overall, a "one-target-fits-all" philosophy may limit the broad clinical benefits of precision dosing. Defining individual-level precision dosing targets may be needed for greatest therapeutic success. Superior future precision dosing targets will integrate several biomarkers that together account for the multiple sources of drug response variability.

First-in-human single-dose study of nizubaglustat, a dual inhibitor of ceramide glucosyltransferase and non-lysosomal glucosylceramidase: Safety, tolerability, pharmacokinetics, and pharmacodynamics of single ascending and multiple doses in healthy adults

Nizubaglustat is a novel, orally available, brain penetrant, potent, and selective dual inhibitor of ceramide glucosyltranferase and non-lysosomal neutral glucosylceramidase (NLGase), which is currently under development for the treatment of subjects with neurological manifestations in primary and secondary gangliosidoses. The objectives of this first-in-human study were to evaluate the safety and tolerability, pharmacokinetics, and pharmacodynamics (PD) of single oral doses of nizubaglustat after single (1, 3, and 9 mg) and multiple oral doses (9 mg once per day (QD) over 14 days) in healthy adults. Nizubaglustat was rapidly absorbed and systemic exposure was dose-proportional. Steady-state was achieved after three days of QD multiple dosing with minimal accumulation. Renal clearance accounted for around 15% of nizubaglustat elimination. Following multiple dosing, plasma concentrations of glucosylceramide (GlcCer), lactosylceramide (LacCer), and monosialodihexosylganglioside (GM3) decreased to a nadir at Day 10. PD target engagement of GCS inhibition was shown by a median decrease from baseline of plasma concentrations of GlcCer, LacCer, and GM3 ganglioside by 70%, 50%, and 48%, respectively. NLGase inhibition was also manifested by increased concentrations of GlcCer in cerebrospinal fluid from Day 1 to Day 14. Nizubaglustat was safe and well-tolerated at all doses tested. Consistent with the high selectivity, and the absence of intestinal disaccharidases inhibition, no cases of diarrhea were reported. No decreased appetite or weight loss was noted. Only treatment-emergent adverse events with preferred terms belonging to the system organ class skin and subcutaneous disorders of mild intensity were reported as drug-related in the nizubaglustat arm, in line with the pharmacological mechanism targeting glucosylceramide metabolism. Taken together, these data support QD dosing of nizubaglustat and its ongoing development in patients with primary and secondary forms of gangliosidoses.

Virtual twin for healthcare management

Healthcare is increasingly fragmented, resulting in escalating costs, patient dissatisfaction, and sometimes adverse clinical outcomes. Strategies to decrease healthcare fragmentation are therefore attractive from payer and patient perspectives. In this commentary, a patient-centered smart phone application called Virtual Twin for Healthcare Management (VTHM) is proposed, including its organizational layout, basic functionality, and potential clinical applications. The platform features a virtual twin hub that displays the body and its health data. This is a physiologically based human model that is "virtualized" for the patient based on their unique genetic, molecular, physiological, and disease characteristics. The spokes of the system are a full service and interoperable electronic-health record, accessible to healthcare providers with permission on any device with internet access. Theoretical case studies based on real scenarios are presented to show how VTHM could potentially improve patient care and clinical efficiency. Challenges that must be overcome to turn VTHM into reality are also briefly outlined. Notably, the VTHM platform is designed to operationalize current and future precision medicine initiatives, such as access to molecular diagnostic results, pharmacogenomics-guided prescribing, and model-informed precision dosing.

Drug-drug interactions that alter the exposure of glucuronidated drugs: Scope, UDP-glucuronosyltransferase (UGT) enzyme selectivity, mechanisms (inhibition and induction), and clinical significance

Drug-drug interactions (DDIs) arising from the perturbation of drug metabolising enzyme activities represent both a clinical problem and a potential economic loss for the pharmaceutical industry. DDIs involving glucuronidated drugs have historically attracted little attention and there is a perception that interactions are of minor clinical relevance. This review critically examines the scope and aetiology of DDIs that result in altered exposure of glucuronidated drugs. Interaction mechanisms, namely inhibition and induction of UDP-glucuronosyltransferase (UGT) enzymes and the potential interplay with drug transporters, are reviewed in detail, as is the clinical significance of known DDIs. Altered victim drug exposure arising from modulation of UGT enzyme activities is relatively common and, notably, the incidence and importance of UGT induction as a DDI mechanism is greater than generally believed. Numerous DDIs are clinically relevant, resulting in either loss of efficacy or an increased risk of adverse effects, necessitating dose individualisation. Several generalisations relating to the likelihood of DDIs can be drawn from the known substrate and inhibitor selectivities of UGT enzymes, highlighting the importance of comprehensive reaction phenotyping studies at an early stage of drug development. Further, rigorous assessment of the DDI liability of new chemical entities that undergo glucuronidation to a significant extent has been recommended recently by regulatory guidance. Although evidence-based approaches exist for the in vitro characterisation of UGT enzyme inhibition and induction, the availability of drugs considered appropriate for use as 'probe' substrates in clinical DDI studies is limited and this should be research priority.

The PRESIDE (PhaRmacogEnomicS In DEpression) Trial: a double-blind randomised controlled trial of pharmacogenomic-informed prescribing of antidepressants on depression outcomes in patients with major depressive disorder in primary care

BACKGROUND

The evidence for the clinical utility of pharmacogenomic (PGx) testing is growing, and guidelines exist for the use of PGx testing to inform prescribing of 13 antidepressants. Although previous randomised controlled trials of PGx testing for antidepressant prescribing have shown an association with remission of depression in clinical psychiatric settings, few trials have focused on the primary care setting, where most antidepressant prescribing occurs.

METHODS

The PRESIDE Trial is a stratified double-blinded randomised controlled superiority trial that aims to evaluate the impact of a PGx-informed antidepressant prescribing report (compared with standard prescribing using the Australian Therapeutic Guidelines) on depressive symptoms after 12 weeks, when delivered in primary care. Six hundred seventy-two patients aged 18-65 years of general practitioners (GPs) in Victoria with moderate to severe depressive symptoms, measured using the Patient Health Questionnaire-9 (PHQ-9), will be randomly allocated 1:1 to each arm using a computer-generated sequence. Participants and GPs will be blinded to the study arm. The primary outcome is a difference between arms in the change of depressive symptoms, measured using the PHQ-9 after 12 weeks. Secondary outcomes include a difference between the arms in change in PHQ-9 score at 4, 8 and 26 weeks, proportion in remission at 12 weeks, a change in side effect profile of antidepressant medications, adherence to antidepressant medications, change in quality of life and cost-effectiveness of the intervention.

DISCUSSION

This trial will provide evidence as to whether PGx-informed antidepressant prescribing is clinically efficacious and cost-effective. It will inform national and international policy and guidelines about the use of PGx to select antidepressants for people with moderate to severe depressive symptoms presenting in primary care.

TRIAL REGISTRATION

Australian and New Zealand Clinical Trial Registry ACTRN12621000181808. Registered on 22 February 2021.

Calculation of the pharmacogenomics benefit score for patients with medication-related problems

Unexpected poor efficacy and intolerable adverse effects are medication-related problems that may result from genetic variation in genes encoding key proteins involved in pharmacokinetics or pharmacodynamics. Pharmacogenomic (PGx) testing can be used in medical practice "pre-emptively" to avoid future patient harm from medications and "reactively" to diagnose medication-related problems following their occurrence. A structured approach to PGx consulting is proposed to calculate the pharmacogenomics benefit score (PGxBS), a patient-centered objective measure of congruency between medication-related problems and patient genotypes. An example case of poor efficacy with multiple medications is presented, together with comments on the potential benefits and limitations of using the PGxBS in medical practice.

Safety, Tolerability, and Pharmacokinetics of IMU-935, a Novel Inverse Agonist of Retinoic Acid Receptor-Related Orphan Nuclear Receptor γt: Results From a Double-Blind, Placebo-Controlled, First-in-Human Phase 1 Study

Retinoic acid receptor-related orphan nuclear receptor (ROR)γt regulates the transcription of interleukin-17 and other cytokines implicated in inflammatory and autoimmune diseases. We assessed the safety, tolerability, and pharmacokinetics (PK) of IMU-935, an inverse agonist of RORγt, in a first-in-human phase 1 study. This was a double-blind, placebo-controlled trial that randomly assigned healthy subjects single ascending doses (25-400 mg) or multiple ascending doses (150 mg once or twice daily for 14 days) of IMU-935 or placebo. Dose escalation was determined by the safety, tolerability, and PK. Twenty-four and 70 subjects received placebo or IMU-935, respectively. Of the 70 subjects who received IMU-935, 59 received a single dose and 11 received multiple doses. Treatment-emergent adverse events (TEAEs) occurred in 21 subjects (88%) and 58 (83%) given any dose of placebo or IMU-935, respectively. Treatment-related TEAEs occurred in 6 (30%) and 25 (42%) subjects given a single dose of placebo and IMU-935, respectively. All treatment-related TEAEs were mild except for 2 moderate TEAEs and 1 moderate TEAE in the IMU-935 group and placebo group, respectively. No treatment-related discontinuations or serious adverse events occurred. The PK of IMU-935 were dose proportional with a half-life of ≈24 hours. In conclusion, IMU-935 was safe with no dose-limiting toxicities and had a PK profile that supports once-daily dosing.

Delineating gene-environment effects using virtual twins of patients treated with clozapine

Studies that focus on individual covariates, while ignoring their interactions, may not be adequate for model-informed precision dosing (MIPD) in any given patient. Genetic variations that influence protein synthesis should be studied in conjunction with environmental covariates, such as cigarette smoking. The aim of this study was to build virtual twins (VTs) of real patients receiving clozapine with interacting covariates related to genetics and environment and to delineate the impact of interacting covariates on predicted clozapine plasma concentrations. Clozapine-treated patients with schizophrenia (N = 42) with observed clozapine plasma concentrations, demographic, environmental, and genotype data were used to construct VTs in Simcyp. The effect of increased covariate virtualization was assessed by performing simulations under three conditions: "low" (demographic), "medium" (demographic and environmental interaction), and "high" (demographic and environmental/genotype interaction) covariate virtualization. Increasing covariate virtualization with interaction improved the coefficient of variation (R² ) from 0.07 in the low model to 0.391 and 0.368 in the medium and high models, respectively. Whereas R² was similar between the medium and high models, the high covariate virtualization model had improved accuracy, with systematic bias of predicted clozapine plasma concentration improving from -138.48 ng/ml to -74.65 ng/ml. A high level of covariate virtualization (demographic, environmental, and genotype) may be required for MIPD using VTs.

Pharmacogenomics in psychiatry - the challenge of cytochrome P450 enzyme phenoconversion and solutions to assist precision dosing

Pharmacogenomic (PGx) testing of cytochrome P450 (CYP) enzymes may improve the efficacy and/or safety of some medications. This is facilitated by increased availability and affordability of genotyping, the development of clinical practice PGx guidelines and regulatory support. However, the common occurrence of CYP phenoconversion, a mismatch between genotype-predicted CYP phenotype and the actual CYP phenotype, currently limits the application of PGx testing for precision dosing in psychiatry. This review proposes a stepwise approach to assist precision dosing in psychiatry via the introduction of PGx stewardship programs and innovative PGx education strategies. A future perspective on delivering precision dosing for psychiatrists is discussed that involves innovative clinical decision support systems powered by model-informed precision dosing.

Liquid Biopsy for Patient Characterization in Cardiovascular Disease: Verification against Markers of Cytochrome P450 and P-Glycoprotein Activities

Precision dosing strategies require accounting for between-patient variability in pharmacokinetics together with subsequent pharmacodynamic differences. Liquid biopsy is a valuable new approach to diagnose disease prior to the appearance of clinical signs and symptoms, potentially circumventing invasive tissue biopsies. However, the possibility of quantitative grading of biomarkers, as opposed to simply confirming their presence or absence, is relatively new. In this study, we aimed to verify expression measurements of cytochrome P450 (CYP) enzymes and the transporter P-glycoprotein (P-gp) in liquid biopsy against genotype and activity phenotype (assessed by the Geneva cocktail approach) in 30 acutely ill patients with cardiovascular disease in a hospital setting. After accounting for exosomal shedding, expression in liquid biopsy correlated with activity phenotype for CYP1A2, CYP2B6, CYP2C9, CYP3A, and P-gp (r = 0.44-0.70, P ≤ 0.05). Although genotype offered a degree of stratification, large variability (coefficient of variation (CV)) in activity (up to 157%) and expression in liquid biopsy (up to 117%) was observed within each genotype, indicating a mismatch between genotype and phenotype. Further, exosome screening revealed expression of 497 targets relevant to drug metabolism and disposition (159 enzymes and 336 transporters), as well as 20 molecular drug targets. Although there were no functional data available to correlate against these large-scale measurements, assessment of disease perturbation from healthy baseline was possible. Verification of liquid biopsy against activity phenotype is important to further individualize modeling approaches that aspire to achieve precision dosing from the start of drug treatment without the need for multiple rounds of dose optimization.

Safety and immunogenicity of a plant-derived rotavirus-like particle vaccine in adults, toddlers and infants

BACKGROUND

This study is the first clinical trial for a parenteral non-replicating rotavirus vaccine developed using virus-like particle (VLP) technology.

METHODS

This open-labeled, randomized, placebo-controlled trial was conducted in two parts: Part A (a first-in-human study in Australian adults) and Part B (ascending dose and descending age in South African adults, toddlers and infants). In Part A, two cohorts of 10 adults were assigned to receive a single intramuscular injection of 1 of 2 escalating dose levels of the rotavirus VLP (Ro-VLP) vaccine (7 μg or 21 μg) or placebo. In Part B, one cohort of 10 adults was assigned to receive a single injection of the Ro-VLP vaccine (21 μg) or placebo, two cohorts of 10 toddlers were assigned to receive 2 injections of 1 of 2 escalating dose levels of the Ro-VLP vaccine (7 μg or 21 μg) or placebo 28 days apart, and three cohorts of 20 infants were assigned to receive 3 injections of 1 of 3 escalating dose levels of the Ro-VLP vaccine (2.5 μg, 7 μg or 21 μg) or placebo or 2 doses of oral Rotarix 28 days apart. Safety, reactogenicity and immunogenicity were assessed.

RESULTS

There were no safety or tolerability concerns after administration of the Ro-VLP vaccine. The Ro-VLP vaccine induced an anti-G1P[8] IgG response in infants 4 weeks after the second and third doses. Neutralizing antibody responses against homologous G1P[8] rotavirus were higher in all Ro-VLP infant groups than in the placebo group 4 weeks after the third dose. No heterotypic immunity was elicited by the Ro-VLP vaccine.

CONCLUSIONS

The Ro-VLP vaccine was well tolerated and induced a homotypic immune response in infants, suggesting that this technology platform is a favorable approach for a parenteral non-replicating rotavirus vaccine.

CLINICAL TRIAL REGISTRATION

NCT03507738.

Attitudes of healthy volunteers to genetic testing in phase 1 clinical trials

Background: Genetic testing in clinical trials introduces several ethical and logistical issues to discuss with potential participants when taking informed consent. The aim of this study was to explore the attitudes of healthy volunteers in phase 1 studies to the topics of genetic security, genetic privacy and incidental genetic findings.

Methods: Healthy volunteers presenting for screening appointments at a phase 1 clinical trial unit (CMAX Clinical Research, Adelaide, Australia) took an anonymous paper survey about genetic testing.

Results: There were 275 respondents to the survey. The mean age was 27 years (range 18-73); 54% were male and 53% were of North/Western European ethnicity. Just over half the healthy volunteers thought genetic security (56%) and genetic privacy (57%) were “important” or “very important”. However, the security of their genetic information was ranked less important than other personal information, including mobile phone number, internet browser search history and email address. Two-thirds of respondents would trade genetic privacy for re-identifiability if information relevant to their health were discovered by genetic testing. Healthy volunteers favoured the return of incidental genetic findings (90% indicated this was “important” or “very important”). A level of risk (10 to 90%) for developing a serious medical condition that would “trigger” the return of incidental genetic findings to participants was not identified.

Conclusions: Healthy volunteers screening for phase 1 clinical trials have mixed views about the importance of genetic security and genetic privacy, but they strongly favour the return of incidental genetic findings that could affect their health. These issues should be discussed with potential participants during informed consent for phase 1 clinical trials with genetic testing.

Model-Informed Drug Development for Anti-Infectives: State of the Art and Future

Model-informed drug development (MIDD) has a long and rich history in infectious diseases. This review describes foundational principles of translational anti-infective pharmacology, including choice of appropriate measures of exposure and pharmacodynamic (PD) measures, patient subpopulations, and drug-drug interactions. Examples are presented for state-of-the-art, empiric, mechanistic, interdisciplinary, and real-world evidence MIDD applications in the development of antibacterials (review of minimum inhibitory concentration-based models, mechanism-based pharmacokinetic/PD (PK/PD) models, PK/PD models of resistance, and immune response), antifungals, antivirals, drugs for the treatment of global health infectious diseases, and medical countermeasures. The degree of adoption of MIDD practices across the infectious diseases field is also summarized. The future application of MIDD in infectious diseases will progress along two planes; "depth" and "breadth" of MIDD methods. "MIDD depth" refers to deeper incorporation of the specific pathogen biology and intrinsic and acquired-resistance mechanisms; host factors, such as immunologic response and infection site, to enable deeper interrogation of pharmacological impact on pathogen clearance; clinical outcome and emergence of resistance from a pathogen; and patient and population perspective. In particular, improved early assessment of the emergence of resistance potential will become a greater focus in MIDD, as this is poorly mitigated by current development approaches. "MIDD breadth" refers to greater adoption of model-centered approaches to anti-infective development. Specifically, this means how various MIDD approaches and translational tools can be integrated or connected in a systematic way that supports decision making by key stakeholders (sponsors, regulators, and payers) across the entire development pathway.

Quantifying the Impact of Phenoconversion on Medications With Actionable Pharmacogenomic Guideline Recommendations in an Acute Aged Persons Mental Health Setting

Introduction: Polypharmacy and genetic variants that strongly influence medication response (pharmacogenomics, PGx) are two well-described risk factors for adverse drug reactions. Complexities arise in interpreting PGx results in the presence of co-administered medications that can cause cytochrome P450 enzyme phenoconversion. Aim: To quantify phenoconversion in a cohort of acute aged persons mental health patients and evaluate its impact on the reporting of medications with actionable PGx guideline recommendations (APRs). Methods: Acute aged persons mental health patients (N = 137) with PGx and medication data at admission and discharge were selected to describe phenoconversion frequencies for CYP2D6, CYP2C19 and CYP2C9 enzymes. The expected impact of phenoconversion was then assessed on the reporting of medications with APRs. Results: Post-phenoconversion, the predicted frequency at admission and discharge increased for CYP2D6 intermediate metabolisers (IMs) by 11.7 and 16.1%, respectively. Similarly, for CYP2C19 IMs, the predicted frequency at admission and discharge increased by 13.1 and 11.7%, respectively. Nineteen medications with APRs were prescribed 120 times at admission, of which 50 (42%) had APRs pre-phenoconversion, increasing to 60 prescriptions (50%) post-phenoconversion. At discharge, 18 medications with APRs were prescribed 122 times, of which 48 (39%) had APRs pre-phenoconversion, increasing to 57 prescriptions (47%) post-phenoconversion. Discussion: Aged persons mental health patients are commonly prescribed medications with APRs, but interpretation of these recommendations must consider the effects of phenoconversion. Adopting a collaborative care model between prescribers and clinical pharmacists should be considered to address phenoconversion and ensure the potential benefits of PGx are maximised.

Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy

Model-informed precision dosing (MIPD) has become synonymous with modern approaches for individualizing drug therapy, in which the characteristics of each patient are considered as opposed to applying a one-size-fits-all alternative. This review provides a brief account of the current knowledge, practices, and opinions on MIPD while defining an achievable vision for MIPD in clinical care based on available evidence. We begin with a historical perspective on variability in dose requirements and then discuss technical aspects of MIPD, including the need for clinical decision support tools, practical validation, and implementation of MIPD in health care. We also discuss novel ways to characterize patient variability beyond the common perceptions of genetic control. Finally, we address current debates on MIPD from the perspectives of the new drug development, health economics, and drug regulations.

Artificial Intelligence and Machine Learning Applied at the Point of Care

Introduction

The increasing availability of healthcare data and rapid development of big data analytic methods has opened new avenues for use of Artificial Intelligence (AI)- and Machine Learning (ML)-based technology in medical practice. However, applications at the point of care are still scarce.

Objective

Review and discuss case studies to understand current capabilities for applying AI/ML in the healthcare setting, and regulatory requirements in the US, Europe and China.

Methods

A targeted narrative literature review of AI/ML based digital tools was performed. Scientific publications (identified in PubMed) and grey literature (identified on the websites of regulatory agencies) were reviewed and analyzed.

Results

From the regulatory perspective, AI/ML-based solutions can be considered medical devices (i.e., Software as Medical Device, SaMD). A case series of SaMD is presented. First, tools for monitoring and remote management of chronic diseases are presented. Second, imaging applications for diagnostic support are discussed. Finally, clinical decision support tools to facilitate the choice of treatment and precision dosing are reviewed. While tested and validated algorithms for precision dosing exist, their implementation at the point of care is limited, and their regulatory and commercialization pathway is not clear. Regulatory requirements depend on the level of risk associated with the use of the device in medical practice, and can be classified into administrative (manufacturing and quality control), software-related (design, specification, hazard analysis, architecture, traceability, software risk analysis, cybersecurity, etc.), clinical evidence (including patient perspectives in some cases), non-clinical evidence (dosing validation and biocompatibility/toxicology) and other, such as e.g. benefit-to-risk determination, risk assessment and mitigation. There generally is an alignment between the US and Europe. China additionally requires that the clinical evidence is applicable to the Chinese population and recommends that a third-party central laboratory evaluates the clinical trial results.

Conclusions

The number of promising AI/ML-based technologies is increasing, but few have been implemented widely at the point of care. The need for external validation, implementation logistics, and data exchange and privacy remain the main obstacles.

Precision dosing to avoid adverse drug reactions

Adverse drug reactions (ADRs) have traditionally been managed by trial and error, adjusting drug and dose selection reactively following patient harm. With an improved understanding of ADRs, and the patient characteristics that increase susceptibility, precision medicine technologies enable a proactive approach to ADRs and support clinicians to change prescribing accordingly. This commentary revisits the famous pharmacology–toxicology continuum first postulated by Paracelsus 500 years ago and explains why precision dosing is needed to help avoid ADRs in modern clinical practice. Strategies on how to improve precision dosing are given, including more research to establish better precision dosing targets in the cases of greatest need, easier access to dosing instructions via e-prescribing, improved monitoring of patients with novel biomarkers of drug response, and further application of model-informed precision dosing.

Precision medicine technology hype or reality? The example of computer-guided dosing

Novel technologies labelled as ‘precision medicine’ are targeting all aspects of clinical care. Whilst some technological advances are undeniably exciting, many doctors at the frontline of healthcare view precision medicine as being out of reach for their patients. Computer-guided dosing is a precision medicine technology that predicts drug concentrations and drug responses based on individual patient characteristics. In this opinion piece, the example of computer-guided dosing is used to illustrate eight features of a precision medicine technology less likely to be hyperbole and more likely to improve patient care. Positive features in this regard include: (1) fitting the definition of ‘precision medicine’; (2) addressing a major clinical problem that negatively impacts patient care; (3) a track record of high-quality medical science published via peer-reviewed literature; (4) well-defined clinical cases for application; (5) quality evidence of benefits measured by various clinical, patient and health economic endpoints; (6) strong economic drivers; (7) user friendliness, including easy integration into clinical workflow, and (8) recognition of importance by patients and their endorsement for broader clinical use. Barriers raised by critics of the approach are given to balance the view. The value of computer-guided dosing will be decided ultimately by the extent to which it can improve cost-effective patient care.

What Does it Take to Make Model-Informed Precision Dosing Common Practice? Report from the 1st Asian Symposium on Precision Dosing

Model-informed precision dosing (MIPD) is modeling and simulation in healthcare to predict the drug dose for a given patient based on their individual characteristics that is most likely to improve efficacy and/or lower toxicity in comparison to traditional dosing. This paper describes the background and status of MIPD and the activities at the 1st Asian Symposium of Precision Dosing. The theme of the meeting was the question, "What does it take to make MIPD common practice?" Formal presentations highlighted the distinction between genetic and non-genetic sources of variability in drug exposure and response, the use of modeling and simulation as decision support tools, and the facilitators to MIPD implementation. A panel discussion addressed the types of models used for MIPD, how the pharmaceutical industry views MIPD, ways to upscale MIPD beyond academic hospital centers, and the essential role of healthcare professional education as a way to progress. The meeting concluded with an ongoing commitment to use MIPD to improve patient care.

Metformin treatment of type 2 diabetes mellitus in pregnancy: update on safety and efficacy

With the increasing prevalence of type 2 diabetes mellitus (T2DM) in women of childbearing age, prescribing antidiabetic medications in first-trimester pregnancy is becoming more common. Metformin treatment during this time is usually avoided in countries with well-resourced healthcare. This is based on historical concerns about safety to the foetus and the widespread availability of insulin. However, there is now increasing interest in the potential benefits of metformin in pregnant women with T2DM. In this commentary, the main evidence supporting metformin safety in pregnancy is summarized, with an emphasis on the first trimester. Based on a structured literature search, the recent randomized controlled trials comparing metformin and insulin are reviewed. We then show that prescribing advice for metformin in pregnancy is inconsistent and product information/package inserts (PI) are universally out of date. This causes confusion and pushes some women and their clinicians to change from metformin to insulin. The potential advantages of metformin in pregnant women with T2DM are then discussed, including oral dosing and improved acceptability, lower resource utilization and cost, decreased insulin requirements, less maternal weight gain and less risk of maternal and neonatal hypoglycaemia. The conclusion is that metformin is a cheap and efficacious antidiabetic medication for many pregnant women with T2DM, with reasonable evidence for safety. Drug information resources should be updated so that metformin can be considered more broadly in women with T2DM who present for antenatal care.

Prediction of olanzapine exposure in individual patients using physiologically based pharmacokinetic modelling and simulation

AIM

The aim of the present study was to predict olanzapine (OLZ) exposure in individual patients using physiologically based pharmacokinetic modelling and simulation (PBPK M&S).

METHODS

A 'bottom-up' PBPK model for OLZ was constructed in Simcyp® (V14.1) and validated against pharmacokinetic studies and data from therapeutic drug monitoring (TDM). The physiological, demographic and genetic attributes of the 'healthy volunteer population' file in Simcyp® were then individualized to create 'virtual twins' of 14 patients. The predicted systemic exposure of OLZ in virtual twins was compared with measured concentration in corresponding patients. Predicted exposures were used to calculate a hypothetical decrease in exposure variability after OLZ dose adjustment.

RESULTS

The pharmacokinetic parameters of OLZ from single-dose studies were accurately predicted in healthy Caucasians [mean-fold errors (MFEs) ranged from 0.68 to 1.14], healthy Chinese (MFEs 0.82 to 1.18) and geriatric Caucasians (MFEs 0.55 to 1.30). Cumulative frequency plots of trough OLZ concentration were comparable between the virtual population and patients in a TDM database. After creating virtual twins in Simcyp®, the R2 values for predicted vs. observed trough OLZ concentrations were 0.833 for the full cohort of 14 patients and 0.884 for the 7 patients who had additional cytochrome P450 2C8 genotyping. The variability in OLZ exposure following hypothetical dose adjustment guided by PBPK M&S was twofold lower compared with a fixed-dose regimen - coefficient of variation values were 0.18 and 0.37, respectively.

CONCLUSIONS

Olanzapine exposure in individual patients was predicted using PBPK M&S. Repurposing of available PBPK M&S platforms is an option for model-informed precision dosing and requires further study to examine clinical potential.

Potential drug-drug interactions with direct oral anticoagulants in elderly hospitalized patients

Background

To determine the prevalence and nature of potential drug-drug interactions (DDIs) with direct oral anticoagulants (DOACs) in elderly hospitalized patients.

Methods

This was a retrospective observational study. Inclusion criteria were: aged over 65 years; taking apixaban, rivaroxaban or dabigatran; and admitted to the Repatriation General Hospital between April 2014 and July 2015. A list of clinically relevant 'perpetrator' drugs was compiled from product information, the Australian Medicines Handbook, the Australian National Prescribing Service resources, and local health network guidelines. The prevalence and nature of potential DDIs with DOACs was determined by comparing inpatient drug charts with the list of perpetrator drugs.

Results

There were 122 patients in the study with a mean age of 82 years. Most patients had nonvalvular atrial fibrillation and were taking DOACs to prevent thrombotic stroke (83%). Overall, 45 patients (37%) had a total of 54 potential DDIs. Thirty-five patients had potential pharmacodynamic DDIs with antidepressants, nonsteroidal anti-inflammatory drugs and antiplatelets (35/122, 29%). Nineteen patients had potential pharmacokinetic DDIs (19/122, 16%). Of these, 68% (13/19) were taking drugs that increase DOAC plasma concentrations (amiodarone, erythromycin, diltiazem or verapamil) and 32% (6/19) were taking drugs that decrease DOAC plasma concentrations (carbamazepine, primidone or phenytoin). There were no cases of patients taking contraindicated interacting drugs.

Discussion

Potential DDIs with DOACs in elderly hospital inpatients are relatively common, particularly interactions that may increase the risk of bleeding. The risk-benefit ratio of DOACs in elderly patients on polypharmacy should always be carefully considered.

Targeted pharmacotherapy after somatic cancer mutation screening

Many patients with solid tumours are treated with targeted pharmacotherapy based on the results of genetic testing ('precision medicine'). This study investigated the use of targeted drugs after OncoFOCUS™+ KIT screening in patients with malignant melanoma, non-small cell lung cancer and metastatic colorectal cancer, and then audited the results against the National Comprehensive Cancer Network (NCCN) guidelines. Patients who were not indicated for targeted pharmacotherapy did not receive such treatment (99%, 100/101). Of the patients indicated for targeted drugs, 79% (33/42) received treatment according to NCCN guidelines. In 48% (20/42) of these patients the results from OncoFOCUS™+ KIT screening were required for targeted drug selection, with the remaining 52% (22/42) prescribed drugs independent of the screening results for various reasons. This study highlights the growing importance of precision medicine approaches in directing pharmacotherapy in medical oncology.

Optimal sampling of antipsychotic medicines: a pharmacometric approach for clinical practice

AIM

To determine optimal sampling strategies to allow the calculation of clinical pharmacokinetic parameters for selected antipsychotic medicines using a pharmacometric approach.

METHODS

This study utilized previous population pharmacokinetic parameters of the antipsychotic medicines aripiprazole, clozapine, olanzapine, perphenazine, quetiapine, risperidone (including 9-OH risperidone) and ziprasidone. d-optimality was utilized to identify time points which accurately predicted the pharmacokinetic parameters (and expected error) of each drug at steady-state. A standard two stage population approach (STS) with MAP-Bayesian estimation was used to compare area under the concentration-time curves (AUC) generated from sparse optimal time points and rich extensive data. Monte Carlo Simulation (MCS) was used to simulate 1000 patients with population variability in pharmacokinetic parameters. Forward stepwise regression analysis was used to determine the most predictive time points of the AUC for each drug at steady-state.

RESULTS

Three optimal sampling times were identified for each antipsychotic medicine. For aripiprazole, clozapine, olanzapine, perphenazine, risperidone, 9-OH risperidone, quetiapine and ziprasidone the CV% of the apparent clearance using optimal sampling strategies were 19.5, 8.6, 9.5, 13.5, 12.9, 10.0, 16.0 and 10.7, respectively. Using the MCS and linear regression approach to predict AUC, the recommended sampling windows were 16.5-17.5 h, 10-11 h, 23-24 h, 19-20 h, 16.5-17.5 h, 22.5-23.5 h, 5-6 h and 5.5-6.5 h, respectively.

CONCLUSION

This analysis provides important sampling information for future population pharmacokinetic studies and clinical studies investigating the pharmacokinetics of antipsychotic medicines.

Metabolic activation of clopidogrel: in vitro data provide conflicting evidence for the contributions of CYP2C19 and PON1

The recent report that clopidogrel efficacy may be more dependent on paraoxonase-1 (PON1) than on cytochrome P450 2C19 (CYP2C19) activity raises questions about the roles of these and other enzymes in clopidogrel activation. To provide insight into the emerging PON1 versus CYP2C19 debate, this commentary summarizes the clinical evidence on the pharmacokinetic determinants of clopidogrel efficacy. We then review the in vitro studies investigating the enzymes involved in clopidogrel activation, and comment on their strengths and limitations. There is agreement amongst in vitro studies regarding the involvement of CYP1A2 and CYP2B6 in the metabolism of clopidogrel to 2-oxo-clopidogrel. However, the evidence for other CYP enzymes in the first activation step (e.g. CYP2C19 and CYP3A4) is inconsistent and dependent on the in vitro test system and laboratory. All major drug metabolizing CYP enzymes are capable of converting 2-oxo-clopidogrel to sulfenic acid intermediates that subsequently form the active thiol metabolite. However, the extent of CYP involvement in this second step has been challenged, and new evidence suggests that CYP-independent hydrolytic cleavage of the thioester bond may be more important than oxidative metabolism.

Predicted metabolic drug clearance with increasing adult age

AIM

To determine the effect of increasing adult age on predicted metabolic drug clearance.

METHOD

Predicted metabolic drug clearances (CLPT ) were determined using in vitro-in vivo extrapolation coupled with physiological-based pharmacokinetic modelling and simulation (IVIVE-PBPK) in Simcyp®. Simulations were conducted using CYP-selective 'probe' drugs with subjects in 5 year age groups (20-25 to 90-95 years). CLPT values were compared with human pharmacokinetic data stratified according to age (young = 20-40 years and elderly = 65-85 years) and gender. Age-related changes in the physiological parameters used for IVIVE of CLPT were described.

RESULTS

Predicted metabolic drug clearances decreased with increasing adult age to approximately 65-70 years: caffeine from 1.5 to 1.0 ml min(-1)  kg(-1) (a 33% decrease), S-warfarin from 0.100 to 0.064 ml min(-1)  kg(-1) (36%), S-mephenytoin from 4.1 to 2.5 ml min(-1)  kg(-1) (39%), desipramine from 10.6 to 7.3 ml min(-1)  kg(-1) (31%) and midazolam from 5.4 to 3.9 ml min(-1)  kg(-1) (27%). Except for S-mephenytoin, predictions were within 3.5-fold of clearances from clinical studies when stratified by age and gender. A trend towards higher CLPT was observed in females, but this was only statistically significant in larger virtual trials. Physiological parameters that determine CLPT decreased with increasing adult age: mean microsomal protein g(-1) of liver, liver weight, hepatic blood flow and human serum albumin concentration.

CONCLUSION

Decreased metabolic clearance in the elderly was predicted by Simcyp® and was generally consistent with limited clinical data for four out of five drugs studied and the broader literature for drugs metabolized by CYP enzymes. IVIVE-PBPK may be increasingly useful in predicting metabolic drug clearance in the elderly.

Considering CYP1A2 phenotype and genotype for optimizing the dose of olanzapine in the management of schizophrenia

INTRODUCTION

Schizophrenia, a mental disorder, is a debilitating condition which typically strikes young people in their early 20's. Antipsychotic medications are widely prescribed for the treatment of schizophrenia however a balancing act is necessary to provide the correct dose to each patient. It is suggested that a large number of patients discontinue antipsychotic pharmacotherapy because the treatments provided do not always reduce the positive symptoms of the disease, while many have adverse effects on the patients. This implies that neither the incorrect drug nor the optimal dosage for that patient is achieved.

AREAS COVERED

The current review investigates variability in response to olanzapine with a specific focus on the common intrinsic and extrinsic factors that influence both olanzapine and CYP1A2 activity. Furthermore, the authors discuss the utilization of phenotyping and genotyping of CYP1A2 and their potential utility in clinical practice for olanzapine dosing regimens. The authors also consider the potential of pharmacometrics compared to pharmacogenomics as a tool to personalize medicine.

EXPERT OPINION

Careful consideration must be given to the impact of a genetic variant on the disposition of a drug prior to implementing genetic 'tests' to determine response. CYP1A2 phenotypic assessment can yield important information regarding the disposition of olanzapine; however, it relies on the accuracy of the metric and the minimal impact of other metabolic pathways. The application of pharmacometrics provides an effective method to establish covariates that significantly influence olanzapine disposition which can incorporate phenotype and/or genotype.

Measurement of human cytochrome P4501A2 (CYP1A2) activity in vitro

Cytochrome P4501A2 (CYP1A2) is responsible for the metabolism of a diverse range of clinically used drugs and dietary and environmental chemicals (including many procarcinogens). CYP1A2 expression is influenced by numerous factors, and hence wide interindividual variability is a characteristic feature of this enzyme in humans. Phenacetin represents a convenient probe for the assessment of human CYP1A2 activity in vitro (hepatic microsomes and recombinant enzyme). It is a relatively high-turnover substrate that forms only one major primary metabolite, the O-deethylated derivative acetaminophen. Acetaminophen formation in incubations of phenacetin with a CYP1A2 source is readily measured by HPLC with UV detection. The assay has a low requirement for human liver microsomes or recombinant enzyme, and is both selective and sensitive without the requirement for a solvent extraction step. Overall assay reproducibility is excellent, with coefficients of variation <4%.