On the anticipation of the human dose in first-in-man trials from preclinical and prior clinical information in early drug development

Current nonclinical approaches for immune assessments of immuno-oncology biotherapeutics

Harnessing the immune system to kill tumors has been revolutionary and, as a result, has had an enormous benefit for patients in extending life and resulting in effective cures in some. However, activation of the immune system can come at the cost of undesirable adverse events such as cytokine release syndrome, immune-related adverse events, on-target/off-tumor toxicity, neurotoxicity and tumor lysis syndrome, which are safety risks that can be challenging to assess non-clinically. This article provides a review of the biology and mechanisms that can result in immune-mediated adverse effects and describes industry approaches using in vitro and in vivo models to aid in the nonclinical safety risk assessments for immune-oncology modalities. Challenges and limitations of knowledge and models are also discussed.

Approaches for estimating the clinical starting dose of new dosage forms: An example of a long-acting injectable formulation of finasteride

In our previous study, a long-acting injectable (LAI) formulation of finasteride was prepared as a new dosage form of PROPECIA®, and in vivo pharmacokinetics (PKs)-pharmacodynamics (PDs) was evaluated in beagle dogs. The resulting PK-PD profiles of the formulation showed pharmacological effects and achievability for monthly delivery. In this study, a first-in-human (FIH) dose of the LAI formulation loaded with finasteride was predicted. The three approaches were used for estimating a FIH dose of the LAI formulation: (1) No observed adverse effect level (NOAEL)-based approach; (2) Pharmacokinetically-guided approach; (3) Pharmacokinetic/pharmacodynamic model-based approach. The advantage, assumptions, limitations, and estimated FIH dose from each approach was discussed and compared since there is no consensus on the best approach. For the prediction of clinical exposures and estimation of FIH doses, the clinical PK-PD parameters were allometrically scaled from the nonclinical data, extracted from reported clinical studies, or fixed from published literature. The starting dose range of the LAI formulation (as finasteride) was estimated to be 16.80-81.06 mg from the three approaches, and the PK/PD model-based approach suggests the most optimal starting dose (16.80 mg) of the LAI formulation. The approaches for estimating starting doses presented in the study could be used as a basis for an Investigational New Drug (IND) application of new dosage forms.

Utility of in silico prediction of target suppression for antibodies against soluble targets: static versus dynamic models

PURPOSE

Antibodies that bind soluble targets such as cytokines belong to an important class of immunotherapies. Target levels can significantly accumulate after antibody administration due to formation of antibody-target complex, accompanied with suppression in free target which is often difficult to measure. Being a surrogate for pharmacodynamic activity, free target suppression is often predicted using in silico tools. The objective of this work is to illustrate the utility of modelling and to compare static versus dynamic models in the prediction of free target suppression.

METHODS

Using binding principles, we have derived a static equation to predict free target suppression at steady state (FTSS). This equation operates with five input parameters and accounts for target accumulation over time. Its predictivity was compared to a dynamic model and to other existing metrics in literature via simulations and assumptions were illustrated.

RESULTS

We demonstrated the utility of in silico tools in prediction of free target suppression using static and dynamic models and clarified the assumptions in key input parameters and their limitations. Predicted values using the FTSS equation correlate very well with those from the dynamic model at level > 20% target suppression, relevant for antagonistic antibodies.

CONCLUSION

In silico tools are needed to predict target suppression by antibody drugs. Static or dynamic models can be used dependant on the scope, available data and undertaken assumptions. These tools can be used to guide discovery and development of antibodies and has the potential to reduce clinical failure.

Flow cytometry and receptor occupancy in immune-oncology

Introduction: Immunotherapies are focused on strategies that alter immune responses, using antibodies that binds to receptors on different immune cell subsets and either activate or suppress their functions depending on the immune response being targeted. Hence, the necessity of developing assays that assess the functional and biological effect of a therapeutic on its target. When incorporated into high-parameter flow cytometry panels, receptor occupancy assay can simultaneously evaluate receptor expression and drug occupancy on defined cell subsets, which can provide information related to functional effects, and safety.Areas covered: This review focuses on the importance of developing, optimizing, and validating a robust Receptor Occupancy Assay (ROA) to improve dose selection, pharmacology monitoring and safety mainly in clinical settings.Expert opinion: The designing of an ROA can be challenging and can lead to exaggerated pharmacology if not accurately developed, optimized, and validated. However, improvements in our understanding of epitopes, binding, affinities, and pharmacological effects may lead to improved antibody drug targeting and receptor evaluation.

A first-in-class, first-in-human, phase I trial of CIGB-552, a synthetic peptide targeting COMMD1 to inhibit the oncogenic activity of NF-κB in patients with advanced solid tumors

CIGB-552 is a synthetic peptide that interacts with COMMD1 and upregulates its protein levels. The objectives of this phase I study were safety, pharmacokinetic profile, evaluation of the lymphocytes CD4+ and CD8+ and preliminary activity in patients with advanced tumors. A 3 + 3 dose-escalation design with seven dose levels was implemented. Patients were included until a grade 3 related adverse event occurred and the maximum tolerated dose was reached. The patients received subcutaneous administration of CIGB-552 three times per week for 2 weeks. Single-dose plasma pharmacokinetics was characterized at two dose levels, and tumor responses were classified by RECIST 1.1. Twenty-four patients received CIGB-552. Dose-limiting toxicity was associated with a transient grade 3 pruritic maculopapular rash at a dose of 7.0 mg. The maximum tolerated dose was defined as 4.7 mg. Ten patients were assessable for immunological status. Seven patients had significant changes in the ratio CD4/CD8 in response to CIGB-552 treatment; three patients did not modify the immunological status. Stable disease was observed in five patients, including two metastatic soft sarcomas. We conclude that CIGB-552 at dose 4.7 mg was well tolerated with no significant adverse events and appeared to provide some clinical benefits.

First in human dose calculation of a single-chain bispecific antibody targeting glioma using the MABEL approach

Background

First-in-human (FIH) clinical trials require careful selection of a safe yet biologically relevant starting dose. Typically, such starting doses are selected based on toxicity studies in a pharmacologically relevant animal model. However, with the advent of target-specific and highly active immunotherapeutics, both the Food and Drug Administration and the European Medicines Agency have provided guidance that recommend determining a safe starting dose based on a minimum anticipated biological effect level (MABEL) approach.

Methods

We recently developed a T cell activating bispecific antibody that effectively treats orthotopic patient-derived malignant glioma and syngeneic glioblastoma in mice (hEGFRvIII:CD3 bi-scFv). hEGFRvIII:CD3 bi-scFv is comprized of two single chain antibody fragments (bi-scFvs) that bind mutant epidermal growth factor receptor variant III (EGFRvIII), a mutation frequently seen in malignant glioma, and human CD3ε on T cells, respectively. In order to establish a FIH dose, we used a MABEL approach to select a safe starting dose for hEGFRvIII:CD3 bi-scFv, based on a combination of in vitro data, in vivo animal studies, and theoretical human receptor occupancy modeling.

Results

Using the most conservative approach to the MABEL assessment, a dose of 57.4 ng hEGFRvIII:CD3 bi-scFv/kg body weight was selected as a safe starting dose for a FIH clinical study.

Conclusions

The comparison of our MABEL-based starting dose to our in vivo efficacious dose and the theoretical human receptor occupancy strongly supports that our human starting dose of 57.4 ng hEGFRvIII:CD3 bi-scFv/patient kg will be safe.

Optimization of hydroxychloroquine dosing scheme based on COVID-19 patients' characteristics: a review of the literature and simulations

During the recent COVID-19 outbreak hydroxychloroquine (HCQ) has been proposed as a safe and effective therapeutic option. However, a wide variety of dosing schemes has been applied in the clinical practice and tested in clinical studies. An extended literature survey was performed investigating the pharmacokinetics, the efficacy and safety of HCQ in COVID-19 treatment. Population pharmacokinetic models were retrieved from the literature and after evaluation and assessment one was selected in order to perform simulations. The most commonly applied dosing schemes were explored for patients with different weights and different levels of HCQ clearance impairment. Model-based simulations of HCQ concentrations revealed that high initial doses followed by low and sparse doses may offer significant benefits to patients by decreasing the viral load without reaching levels considered to produce adverse effects. For instance, the dosing scheme proposed for a 70 kg adult with moderate COVID-19 symptoms would be 600 mg upon diagnosis, 400 mg after 12 h, 300 mg after 24 h, 200 mg after 36 h, followed by 200 mg BID for 4 d, followed by 200 mg OD for 5 d. Based on the results from simulations performed and the currently published knowledge regarding HCQ in COVID-19 treatment, this study provides evidence that a high loading dose followed by sparse doses could offer significant benefits to the patients.

'In silico' toxicology methods in drug safety assessment

While experimental animal investigation has historically been the most conventional approach conducted to assess drug safety and is currently considered the main method for determining drug toxicity, these studies are constricted by cost, time, and ethical approvals. Over the last 20 years, there have been significant advances in computational sciences and computer data processing, while knowledge of alternative techniques and their application has developed into a valuable skill in toxicology. Thus, the application of in silico methods in drug safety assessment is constantly increasing. They are very complex and are grounded on accumulated knowledge from toxicology, bioinformatics, biochemistry, statistics, mathematics, as well as molecular biology. This review will summarize current state-of-the-art scientific data on the use of in silico methods in toxicity testing, taking into account their shortcomings, and highlighting the strategies that should deliver consistent results, while covering the applications of in silico methods in preclinical trials and drug impurities toxicity testing.

Model-Informed Drug Development for Antimicrobials: Translational PK and PK/PD Modeling to Predict an Efficacious Human Dose for Apramycin

Apramycin represents a subclass of aminoglycoside antibiotics that has been shown to evade almost all mechanisms of clinically relevant aminoglycoside resistance. Model-informed drug development may facilitate its transition from preclinical to clinical phase. This study explored the potential of pharmacokinetic/pharmacodynamic (PK/PD) modeling to maximize the use of in vitro time-kill and in vivo preclinical data for prediction of a human efficacious dose (HED) for apramycin. PK model parameters of apramycin from four different species (mouse, rat, guinea pig, and dog) were allometrically scaled to humans. A semimechanistic PK/PD model was developed from the rich in vitro data on four Escherichia coli strains and subsequently the sparse in vivo efficacy data on the same strains were integrated. An efficacious human dose was predicted from the PK/PD model and compared with the classical PK/PD index methodology and the aminoglycoside dose similarity. One-compartment models described the PK data and human values for clearance and volume of distribution were predicted to 7.07 L/hour and 26.8 L, respectively. The required fAUC/MIC (area under the unbound drug concentration-time curve over MIC ratio) targets for stasis and 1-log kill in the thigh model were 34.5 and 76.2, respectively. The developed PK/PD model predicted the efficacy data well with strain-specific differences in susceptibility, maximum bacterial load, and resistance development. All three dose prediction approaches supported an apramycin daily dose of 30 mg/kg for a typical adult patient. The results indicate that the mechanistic PK/PD modeling approach can be suitable for HED prediction and serves to efficiently integrate all available efficacy data with potential to improve predictive capacity.

Strategies and Recommendations for Using a Data-Driven and Risk-Based Approach in the Selection of First-in-Human Starting Dose: An International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) Assessment

Various approaches to first-in-human (FIH) starting dose selection for new molecular entities (NMEs) are designed to minimize risk to trial subjects. One approach uses the minimum anticipated biological effect level (MABEL), which is a conservative method intended to maximize subject safety and designed primarily for NMEs having high perceived safety risks. However, there is concern that the MABEL approach is being inappropriately used for lower risk molecules with negative impacts on drug development and time to patient access. In addition, ambiguity exists in how MABEL is defined and the methods used to determine it. The International Consortium for Innovation and Quality in Pharmaceutical Development convened a working group to understand current use of MABEL and its impact on FIH starting dose selection, and to make recommendations for FIH dose selection going forward. An industry-wide survey suggested the achieved or estimated maximum tolerated dose, efficacious dose, or recommended phase II dose was > 100-fold higher than the MABEL-based starting dose for approximately one third of NMEs, including trials in patients. A decision tree and key risk factor table were developed to provide a consistent, data driven-based, and risk-based approach for selecting FIH starting doses.

First-in-human dose: current status review for better future perspectives

AIM

The aim of this article is to understand the pros and cons of various methods involved in first-in-human (FIH) dose calculation and act decisively in dose escalations when calculating the maximum tolerated dose.

SUBJECTS AND METHODS

We reviewed early phase clinical trials for methods of FIH dose and dose-escalation steps and discuss them in line with existing guidelines. We also reviewed the clinical trial registry to recognize trends in trial registration in recent years and after a massive failure in a few trials.

RESULTS

Phase 1 trials of TGN 1412 and BIA10-2474 would always be remembered as catastrophes for pharmaceutical development plans. Quite often than not, healthy human volunteers are the guinea pigs in this stage of drug development. And, the most important aspect of designing an early phase study is deciding upon the dose to be started with, apart from the selection of cohort and escalation steps. The common principles used for FIH dose calculation include no observed adverse effect level, minimum anticipated biological effect level, pharmacologically active dose, pharmacokinetic/pharmacodynamic approach, and similar drug comparison approach.

CONCLUSION

Early phase clinical trials are basically foundation stones on which lies the entire onus of the later stages of development. Deciding FIH dose is a crucial step that necessitates the incorporation of detailed data from the preclinical stages and application of the most conservative approach for the safety/benefit of the volunteers in these studies.

Application of a MABEL Approach for a T-Cell-Bispecific Monoclonal Antibody: CEA TCB

CEA TCB is a novel T-cell-bispecific (TCB) antibody targeting the carcinoembryonic antigen (CEA) expressed on tumor cells and the CD3 epsilon chain (CD3e) present on T cells, which is currently in Phase 1 clinical trials (NCT02324257) for the treatment of CEA-positive solid tumors. Because the human CEA (hCEA) binder of CEA TCB does not cross-react with cynomolgus monkey and CEA is absent in rodents, alternative nonclinical safety evaluation approaches were considered. These included the development of a cynomolgus monkey cross-reactive homologous (surrogate) antibody (cyCEA TCB) for its evaluation in cynomolgus monkey and the development of double-transgenic mice, expressing hCEA and human CD3e (hCEA/hCD3e Tg), as a potential alternative species for nonclinical safety studies. However, a battery of nonclinical in vitro/ex vivo experiments demonstrated that neither of the previous approaches provided a suitable and pharmacologically relevant model to assess the safety of CEA TCB. Therefore, an alternative approach, a minimum anticipated biological effect level (MABEL), based on an in vitro tumor lysis assay was used to determine the starting dose for the first-in-human study. Using the most conservative approach to the MABEL assessment, a dose of 52 μg was selected as a safe starting dose for clinical study.

Translating QT interval prolongation from conscious dogs to humans

AIM

In spite of screening procedures in early drug development, uncertainty remains about the propensity of new chemical entities (NCEs) to prolong the QT/QTc interval. The evaluation of proarrhythmic activity using a comprehensive in vitro proarrhythmia assay does not fully account for pharmacokinetic-pharmacodynamic (PKPD) differences in vivo. In the present study, we evaluated the correlation between drug-specific parameters describing QT interval prolongation in dogs and in humans.

METHODS

Using estimates of the drug-specific parameter, data on the slopes of the PKPD relationships of nine compounds with varying QT-prolonging effects (cisapride, sotalol, moxifloxacin, carabersat, GSK945237, SB237376 and GSK618334, and two anonymized NCEs) were analysed. Mean slope estimates varied between -0.98 ms μM-1 and 6.1 ms μM-1 in dogs and -10 ms μM-1 and 90 ms μM-1 in humans, indicating a wide range of effects on the QT interval. Linear regression techniques were then applied to characterize the correlation between the parameter estimates across species.

RESULTS

For compounds without a mixed ion channel block, a correlation was observed between the drug-specific parameter in dogs and humans (y = -1.709 + 11.6x; R2  = 0.989). These results show that per unit concentration, the drug effect on the QT interval in humans is 11.6-fold larger than in dogs.

CONCLUSIONS

Together with information about the expected therapeutic exposure, the evidence of a correlation between the compound-specific parameter in dogs and in humans represents an opportunity for translating preclinical safety data before progression into the clinic. Whereas further investigation is required to establish the generalizability of our findings, this approach can be used with clinical trial simulations to predict the probability of QT prolongation in humans.

Pharmacokinetic/Pharmacodynamic Modeling of the PDE4 Inhibitor TAK-648 in Type 2 Diabetes: Early Translational Approaches for Human Dose Prediction

TAK‐648 is a PDE4 inhibitor with demonstrated preclinical antidiabetic properties. Our objective was to develop a translational pharmacokinetic/pharmacodynamic (PK/PD) model for human type 2 diabetes (T2D) dose prediction using HbA_1c results from a db/db mouse study. Estimated parameters in combination with tPDE4i values calculated for the clinical roflumilast dose of 500 μg were used to translate preclinical effects of TAK‐648 to required exposure in humans. A first‐in‐human study with single TAK‐648 doses of 0.05–0.85 mg in healthy volunteers yielded mean maximum TAK‐648 concentrations (Cmax) and area under the curve (AUC) values from 0.62–11.9 μg/L and 4.58–93.8 μg*h/L, respectively. Based on the performed pharmacokinetic/pharmacodynamic analysis and clinical PK results, clinical efficacy would be expected at a daily dose of 0.1 mg, which is well within the investigated clinical dose range. This result significantly enhanced the confidence in TAK‐648 for type 2 diabetes treatment and underlines the necessity of translational approaches in early preclinical phases.

Determination of the starting dose in the first-in-human clinical trials with monoclonal antibodies: a systematic review of papers published between 1990 and 2013

A systematic review was performed to evaluate how the maximum recommended starting dose (MRSD) was determined in first-in-human (FIH) studies with monoclonal antibodies (mAbs). Factors associated with the choice of each MRSD determination method were also identified. PubMed was searched for FIH studies with mAbs published in English between January 1, 1990 and December 31, 2013, and the following information was extracted: MRSD determination method, publication year, therapeutic area, antibody type, safety factor, safety assessment results after the first dose, and number of dose escalation steps. Seventy-nine FIH studies with mAbs were identified, 49 of which clearly reported the MRSD determination method. The no observed adverse effects level (NOAEL)-based approach was the most frequently used method, whereas the model-based approach was the least commonly used method (34.7% vs 16.3%). The minimal anticipated biological effect level (MABEL)- or minimum effective dose (MED)-based approach was used more frequently in 2011–2013 than in 1990–2007 (31.6% vs 6.3%, P=0.036), reflecting a slow, but steady acceptance of the European Medicines Agency’s guidance on mitigating risks for FIH clinical trials (2007). The median safety factor was much lower for the MABEL- or MED-based approach than for the other MRSD determination methods (10 vs 32.2–53). The number of dose escalation steps was not significantly different among the different MRSD determination methods. The MABEL-based approach appears to be safer and as efficient as the other MRSD determination methods for achieving the objectives of FIH studies with mAbs faster.

Physiologically-based modeling to predict the clinical behavior of monoclonal antibodies directed against lymphocyte antigens

Many clinically approved and investigational monoclonal antibody (mAb)-based therapeutics are directed against proteins located in the systemic circulation, including cytokines, growth factors, lymphocyte proteins, and shed antigens. Interaction between mAb and target may lead to non-linear pharmacokinetics (PK), characterized by rapid, target-mediated elimination. Several groups have reported that determinants of target-mediated elimination could include mAb-target binding, target expression, and target turnover. Recently, we scaled a physiologically-based pharmacokinetic model for mAb disposition to man and used it to predict the non-linear PK of mAbs directed against tumor epithelial proteins. In this work, we extended the previously described model to account for the influence of lymphocyte proteins on mAb PK in man. To account for the dynamic behavior of lymphocytes in the circulation, lymphocyte cycling between blood and lymphoid organs was described using first-order transfer rate constants. Use of lymphocyte cycling and reported target turnover rates in the model allowed the accurate prediction of the pharmacokinetics and pharmacodynamics (PD) of 4 mAbs (TRX1, MTRX1011a, rituximab, daclizumab) directed against 3 lymphocyte targets (CD4, CD20, CD25). The results described here suggest that the proposed model structure may be useful in the a priori prediction of the PK/PD properties of mAbs directed against antigens in the circulation.

GetReal in mathematical modelling: a review of studies predicting drug effectiveness in the real world

The performance of a drug in a clinical trial setting often does not reflect its effect in daily clinical practice. In this third of three reviews, we examine the applications that have been used in the literature to predict real‐world effectiveness from randomized controlled trial efficacy data. We searched MEDLINE, EMBASE from inception to March 2014, the Cochrane Methodology Register, and websites of key journals and organisations and reference lists. We extracted data on the type of model and predictions, data sources, validation and sensitivity analyses, disease area and software. We identified 12 articles in which four approaches were used: multi‐state models, discrete event simulation models, physiology‐based models and survival and generalized linear models. Studies predicted outcomes over longer time periods in different patient populations, including patients with lower levels of adherence or persistence to treatment or examined doses not tested in trials. Eight studies included individual patient data. Seven examined cardiovascular and metabolic diseases and three neurological conditions. Most studies included sensitivity analyses, but external validation was performed in only three studies. We conclude that mathematical modelling to predict real‐world effectiveness of drug interventions is not widely used at present and not well validated. © 2016 The Authors Research Synthesis Methods Published by John Wiley & Sons Ltd.

Pharmacology-based toxicity assessment: towards quantitative risk prediction in humans

Despite ongoing efforts to better understand the mechanisms underlying safety and toxicity, ~30% of the attrition in drug discovery and development is still due to safety concerns. Changes in current practice regarding the assessment of safety and toxicity are required to reduce late stage attrition and enable effective development of novel medicines. This review focuses on the implications of empirical evidence generation for the evaluation of safety and toxicity during drug development. A shift in paradigm is needed to (i) ensure that pharmacological concepts are incorporated into the evaluation of safety and toxicity; (ii) facilitate the integration of historical evidence and thereby the translation of findings across species as well as between in vitro and in vivo experiments and (iii) promote the use of experimental protocols tailored to address specific safety and toxicity questions. Based on historical examples, we highlight the challenges for the early characterisation of the safety profile of a new molecule and discuss how model-based methodologies can be applied for the design and analysis of experimental protocols. Issues relative to the scientific rationale are categorised and presented as a hierarchical tree describing the decision-making process. Focus is given to four different areas, namely, optimisation, translation, analytical construct and decision criteria. From a methodological perspective, the relevance of quantitative methods for estimation and extrapolation of risk from toxicology and safety pharmacology experimental protocols, such as points of departure and potency, is discussed in light of advancements in population and Bayesian modelling techniques (e.g. non-linear mixed effects modelling). Their use in the evaluation of pharmacokinetics (PK) and pharmacokinetic-pharmacodynamic relationships (PKPD) has enabled great insight into the dose rationale for medicines in humans, both in terms of efficacy and adverse events. Comparable benefits can be anticipated for the assessment of safety and toxicity profile of novel molecules.

Pharmacokinetics in Drug Discovery: An Exposure-Centred Approach to Optimising and Predicting Drug Efficacy and Safety

The role of pharmacokinetics (PK) in drug discovery is to support the optimisation of the absorption, distribution, metabolism and excretion (ADME) properties of lead compounds with the ultimate goal to attain a clinical candidate which achieves a concentration-time profile in the body that is adequate for the desired efficacy and safety profile. A thorough characterisation of the lead compounds aiming at the identification of the inherent PK liabilities also includes an early generation of PK/PD relationships linking in vitro potency and target exposure/engagement with expression of pharmacological activity (mode-of-action) and efficacy in animal studies. The chapter describes an exposure-centred approach to lead generation, lead optimisation and candidate selection and profiling that focuses on a stepwise generation of an understanding between PK/exposure and PD/efficacy relationships by capturing target exposure or surrogates thereof and cellular mode-of-action readouts in vivo. Once robust PK/PD relationship in animal PD models has been constructed, it is translated to anticipate the pharmacologically active plasma concentrations in patients and the human therapeutic dose and dosing schedule which is also based on the prediction of the PK behaviour in human as described herein. The chapter outlines how the level of confidence in the predictions increases with the level of understanding of both the PK and the PK/PD of the new chemical entities (NCE) in relation to the disease hypothesis and the ability to propose safe and efficacious doses and dosing schedules in responsive patient populations. A sound identification of potential drug metabolism and pharmacokinetics (DMPK)-related development risks allows proposing of an effective de-risking strategy for the progression of the project that is able to reduce uncertainties and to increase the probability of success during preclinical and clinical development.

Receptor occupancy assessment by flow cytometry as a pharmacodynamic biomarker in biopharmaceutical development

Receptor occupancy (RO) assays are designed to quantify the binding of therapeutics to their targets on the cell surface and are frequently used to generate pharmacodynamic (PD) biomarker data in nonclinical and clinical studies of biopharmaceuticals. When combined with the pharmacokinetic (PK) profile, RO data can establish PKPD relationships, which are crucial for informing dose decisions. RO is commonly measured by flow cytometry on fresh blood specimens and is subject to numerous technical and logistical challenges. To ensure that reliable and high quality results are generated from RO assays, careful assay design, key reagent characterization, data normalization/reporting, and thorough planning for implementation are of critical importance during development. In this article, the authors share their experiences and perspectives in these areas and discuss challenges and potential solutions when developing and implementing a flow cytometry‐based RO method in support of biopharmaceutical drug development. © 2015 The Authors Cytometry Part B: Clinical Cytometry Published by Wiley Periodicals, Inc.

Electroencephalography and analgesics

To assess centrally mediated analgesic mechanisms in clinical trials with pain patients, objective standardized methods such as electroencephalography (EEG) has many advantages. The aim of this review is to provide the reader with an overview of present findings in analgesics assessed with spontaneous EEG and evoked brain potentials (EPs) in humans. Furthermore, EEG methodologies will be discussed with respect to translation from animals to humans and future perspectives in predicting analgesic efficacy. We searched PubMed with MeSH terms 'analgesics', 'electroencephalography' and 'evoked potentials' for relevant articles. Combined with a search in their reference lists 15 articles on spontaneous EEG and 55 papers on EPs were identified. Overall, opioids produced increased activity in the delta band in the spontaneous EEG, but increases in higher frequency bands were also seen. The EP amplitudes decreased in the majority of studies. Anticonvulsants used as analgesics showed inconsistent results. The N-methyl-D-aspartate receptor antagonist ketamine showed an increase in the theta band in spontaneous EEG and decreases in EP amplitudes. Tricyclic antidepressants increased the activity in the delta, theta and beta bands in the spontaneous EEG while EPs were inconsistently affected. Weak analgesics were mainly investigated with EPs and a decrease in amplitudes was generally observed. This review reveals that both spontaneous EEG and EPs are widely used as biomarkers for analgesic drug effects. Methodological differences are common and a more uniform approach will further enhance the value of such biomarkers for drug development and prediction of treatment response in individual patients.

ATP-dependent transport of statins by human and rat MRP2/Mrp2

Multidrug resistance associated protein-2, MRP2 (human), Mrp2 (rat) are an efflux transporter, responsible for the transport of numerous endogenous and xenobiotic compounds including taurocholate, methotrexate and carboxydichlorofluorescein (CDF). The present study aims to characterise transport of statins by human and rat MRP2/Mrp2 using membrane and vesicle preparations. All statins tested (simvastatin, pravastatin, pitavastatin, fluvastatin, atorvastatin, lovastatin and rosuvastatin) stimulated vanadate-sensitive ATPase activity in membranes expressing human or rat MRP2/Mrp2, suggesting that all statins are substrates of human and rat MRP2/Mrp2. The substrate affinity (Km) of all statins for MRP2/Mrp2 was comparable and no correlation between lipophilicity (logD7.0) and Km was seen. All statins also inhibited uptake of the fluorescent Mrp2 substrate, CDF (1μM) into vesicles expressing human or rat MRP2/Mrp2 with similar IC50 values. Fitting of the inhibitory data to the hill slope equation, gave hill coefficients (h) of greater than one, suggesting that transport involved more than one binding site for inhibitors of MPR2 and Mrp2. We conclude that statins were transported by both human and rat MRP2/Mrp2 with similar affinity. Statins were also shown to compete with other substrates for transport by MRP2/Mrp2 and that this transport involved more than one binding site on the Mrp2/MRP2 protein.

Bioanalysis of target biomarker and PK/PD relevancy during the development of biotherapeutics

The majority of biotherapeutic drugs act on specific targets, which may serve as biomarkers to be evaluated for target engagement and validation. Together with subsequent pathway biomarkers, these data can provide proof-of-mechanism and understanding of the biological drug affect. A major task during early development is to predict, for the first first time in human clinical trials, the starting dose and simulate the PK/PD relationship. However, determinations of the biotherapeutic drug and target concentrations are not straightforward due to temporal changes of drug–target binding and challenges in developing reliable methods to measure the free and total drug and target. Herein, the bioanalysis of the target biomarker and the biotherapeutics in the context of PK/PD relevancy during drug development is reviewed. Binding of the target to the biotherapeutic will affect target clearance and drug disposition, resulting in nonlinear PK. Reliable and specific methods are crucial for the correct PK/PD modeling and interpretation.

Human experimental pain models for assessing the therapeutic efficacy of analgesic drugs

Pain models in animals have shown low predictivity for analgesic efficacy in humans, and clinical studies are often very confounded, blurring the evaluation. Human experimental pain models may therefore help to evaluate mechanisms and effect of analgesics and bridge findings from basic studies to the clinic. The present review outlines the concept and limitations of human experimental pain models and addresses analgesic efficacy in healthy volunteers and patients. Experimental models to evoke pain and hyperalgesia are available for most tissues. In healthy volunteers, the effect of acetaminophen is difficult to detect unless neurophysiological methods are used, whereas the effect of nonsteroidal anti-inflammatory drugs could be detected in most models. Anticonvulsants and antidepressants are sensitive in several models, particularly in models inducing hyperalgesia. For opioids, tonic pain with high intensity is attenuated more than short-lasting pain and nonpainful sensations. Fewer studies were performed in patients. In general, the sensitivity to analgesics is better in patients than in healthy volunteers, but the lower number of studies may bias the results. Experimental models have variable reliability, and validity shall be interpreted with caution. Models including deep, tonic pain and hyperalgesia are better to predict the effects of analgesics. Assessment with neurophysiologic methods and imaging is valuable as a supplement to psychophysical methods and can increase sensitivity. The models need to be designed with careful consideration of pharmacological mechanisms and pharmacokinetics of analgesics. Knowledge obtained from this review can help design experimental pain studies for new compounds entering phase I and II clinical trials.

Applications of human pharmacokinetic prediction in first-in-human dose estimation

Quantitative estimations of first-in-human (FIH) doses are critical for phase I clinical trials in drug development. Human pharmacokinetic (PK) prediction methods have been developed to project the human clearance (CL) and bioavailability with reasonable accuracy, which facilitates estimation of a safe yet efficacious FIH dose. However, the FIH dose estimation is still very challenging and complex. The aim of this article is to review the common approaches for FIH dose estimation with an emphasis on PK-guided estimation. We discuss 5 methods for FIH dose estimation, 17 approaches for the prediction of human CL, 6 methods for the prediction of bioavailability, and 3 tools for the prediction of PK profiles. This review may serve as a practical protocol for PK- or pharmacokinetic/pharmacodynamic-guided estimation of the FIH dose.

Monoclonal antibodies: what are the pharmacokinetic and pharmacodynamic considerations for drug development?

INTRODUCTION

The number of monoclonal antibodies available for clinical use and under development has dramatically increased in the last 10 years. Understanding their pharmacokinetics and pharmacodynamics is essential for selecting the right clinical candidate, correct dose and regimen for a target indication.

AREAS COVERED

This article reviews the existing literature and knowledge of monoclonal antibodies. Specifically, the authors discuss monoclonal antibodies with respect to their pharmacokinetics (including absorption, distribution and elimination) and their pharmacodynamics. The authors also look at the pharmacokinetic/pharmacodynamic relationship, scaling from preclinical to clinical studies and selection of the first-in-human dose.

EXPERT OPINION

Monoclonal antibodies have complex pharmacokinetic and pharmacodynamic characteristics that are dependent on several factors. Therefore, it is important to improve our understanding of the pharmacokinetics and pharmacodynamics of monoclonal antibodies from a basic research standpoint. It is also equally important to apply mechanistic pharmacokinetic/pharmacodynamic models to interpret the experimental results and facilitate efforts to predict the safety and efficacy of monoclonal antibodies.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 4: prediction of plasma concentration-time profiles in human from in vivo preclinical data by using the Wajima approach

The objective of this study was to evaluate the performance of the Wajima allometry (Css -MRT) approach published in the literature, which is used to predict the human plasma concentration-time profiles from a scaling of preclinical species data. A diverse and blinded dataset of 108 compounds from PhRMA member companies was used in this evaluation. The human intravenous (i.v.) and oral (p.o.) pharmacokinetics (PK) data were available for 18 and 107 drugs, respectively. Three different scenarios were adopted for prediction of human PK profiles. In the first scenario, human clearance (CL) and steady-state volume of distribution (Vss ) were predicted by unbound fraction corrected intercept method (FCIM) and Øie-Tozer (OT) approaches, respectively. Quantitative structure activity relationship (QSAR)-based approaches (TSrat-dog ) based on compound descriptors together with rat and dog data were utilized in the second scenario. Finally, in the third scenario, CL and Vss were predicted using the FCIM and Jansson approaches, respectively. For the prediction of oral pharmacokinetics, the human bioavailability and absorption rate constant were assumed as the average of preclinical species. Various statistical techniques were used for assessing the accuracy of the simulation scenarios. The human CL and Vss were predicted within a threefold error range for about 75% of the i.v. drugs. However, the accuracy in predicting key p.o. PK parameters appeared to be lower with only 58% of simulations falling within threefold of observed parameters. The overall ability of the Css -MRT approach to predict the curve shape of the profile was in general poor and ranged between low to medium level of confidence for most of the predictions based on the selected criteria.

Comparative evaluation of US Food and Drug Administration and pharmacologically guided approaches to determine the maximum recommended starting dose for first-in-human clinical trials in adult healthy men

The authors compared US Food and Drug Administration (FDA) and 9 pharmacologically guided approaches (PGAs; simple allometry, maximum life span potential [MLP], brain weight, rule of exponent [ROE], two 2-sp methods and 3 one-sp methods) to determine the maximum recommended starting dose (MRSD) for first-in-human clinical trials in adult healthy men using 10 drugs. The ROE method as suggested by Mahmood and Balian1 gave the best prediction accuracy for a pharmacokinetic (PK) parameter. Values derived from clearance were consistently better than volume of distribution (Vd)-based methods and had lower root mean square error (RMSE) values. A pictorial method evaluation chart was developed based on fold errors for simultaneous evaluation of various methods. The one-sp method (rat) and the US FDA methods gave the highest prediction accuracy and low RMSE values, and the 2-sp methods gave the least prediction accuracy with high RMSE values. The ROE method gave more consistent predictions for PK parameters than other allometric methods. Despite this, the MRSD predictions were not better than US FDA methods, probably indicating that across-species variation in clearance may be higher than variation in no observed adverse effect level (NOAEL) and that PGA methods may not be consistently better than the NOAEL based methods.

Prediction of exposure-response relationships to support first-in-human study design

In drug development, phase 1 first-in-human studies represent a major milestone as the drug moves from preclinical discovery to clinical development activities. The safety of human subjects is paramount to the conduct of these studies and regulatory considerations guide activities. Forces of evolution on the pharmaceutical industry are re-shaping the first-in-human dose selection strategy. Namely, high attrition rates in part due to lack of efficacy have led to the re-organization of research and development organizations around the umbrella of translational research. Translational research strives to bring basic research advances into the clinic and support the reverse transfer of information to enhance compound selection strategies. Pharmacokinetic/pharmacodynamic (PK/PD) modeling holds a unique position in translational research by attempting to integrate diverse sets of information. PK/PD modeling has demonstrated utility in dose selection and trial design for later stages of drug development and is now being employed with greater prevalence in the translational research setting to manage risk (i.e., oncology and inflammation/immunology). Moving from empirical E (max) models to more mechanistic representations of the biological system, a higher fidelity of human predictions is expected. Strategies that have proven useful for PK predictions are being applied to PK/PD predictions. This review article examines examples of the application of PK/PD modeling in establishing target concentrations for supporting first-in-human study design.

A brief survey of first-in-human studies

First-in-human (FIH) studies are a critical step in the drug development process and typically aim to characterize a compound's pharmacokinetics, potential effective concentration or dose, and safety or tolerability margins. Although effort continues to enhance the predictive quality of the selection of FIH doses from preclinical data, and little consensus is available on the design and conduct of FIH studies, detailed surveys describing general approaches taken in FIH studies are useful in the optimization of early-phase clinical drug development. Although allometric scaling techniques continue to provide poor predictive estimates for human pharmacokinetic parameters, FIH starting doses are selected with substantial safety factors applied to human equivalent dose, often in excess of regulatory guidelines. Based on these examples, it appears that relatively conservative 2-fold dose escalations are the most common escalation approach within FIH single ascending dose studies. The combination of conservative dose escalations with low starting doses can result in large FIH trials, consuming both time and resources. Approaches that could enhance the predictive nature of a compound's disposition and adaptive nature of FIH studies could provide a tremendous benefit for drug development.

The Simcyp population-based ADME simulator

The Simcyp population-based absorption, distribution, metabolism and excretion simulator is a platform and database for 'bottom-up' mechanistic modelling and simulation of the processes of oral absorption, tissue distribution, metabolism and excretion of drugs and drug candidates in healthy and disease populations. It combines experimental data generated routinely during preclinical drug discovery and development from in vitro enzyme and cellular systems and relevant physicochemical attributes of compound and dosage form with demographic, physiological and genetic information on different patient populations. The mechanistic approach implemented in the Simcyp Simulator allows simulation of complex absorption, distribution, metabolism and excretion outcomes, particularly those involving multiple drug interactions, parent drug and metabolite profiles and time- and dose-dependent phenomena such as auto-induction and auto-inhibition.This review describes the framework and organisation of the simulator and how it combines the different categories of information.

Safety and immunotoxicity assessment of immunomodulatory monoclonal antibodies

Most therapeutic monoclonal antibodies (mAbs) licensed for human use or in clinical development are indicated for treatment of patients with cancer and inflammatory/autoimmune disease and as such, are designed to directly interact with the immune system. A major hurdle for the development and early clinical investigation of many of these immunomodulatory mAbs is their inherent risk for adverse immune-mediated drug reactions in humans such as infusion reactions, cytokine storms, immunosuppression and autoimmunity. A thorough understanding of the immunopharmacology of a mAb in humans and animals is required to both anticipate the clinical risk of adverse immunotoxicological events and to select a safe starting dose for first-in-human (FIH) clinical studies. This review summarizes the most common adverse immunotoxicological events occurring in humans with immunomodulatory mAbs and outlines non-clinical strategies to define their immunopharmacology and assess their immunotoxic potential, as well as reduce the risk of immunotoxicity through rational mAb design. Tests to assess the relative risk of mAb candidates for cytokine release syndrome, innate immune system (dendritic cell) activation and immunogenicity in humans are also described. The importance of selecting a relevant and sensitive toxicity species for human safety assessment in which the immunopharmacology of the mAb is similar to that expected in humans is highlighted, as is the importance of understanding the limitations of the species selected for human safety assessment and supplementation of in vivo safety assessment with appropriate in vitro human assays. A tiered approach to assess effects on immune status, immune function and risk of infection and cancer, governed by the mechanism of action and structural features of the mAb, is described. Finally, the use of immunopharmacology and immunotoxicity data in determining a minimum anticipated biologic effect Level (MABEL) and in the selection of safe human starting dose is discussed.

Applying physiological and biochemical concepts to optimize biological drug development

Posology--the science of dose and regimen--is a critical part of drug development. It is concerned with ensuring that patients experience significant clinical benefit without intolerable adverse effects. It has become apparent, in the case of certain biologics, that one can directly quantitate occupancy or target capture and relate these to clinical responses. With mathematical models that integrate binding concepts with clinical effects, potential posologies can be quickly explored through simulation, thereby liberating research teams from the traditional constraints and simultaneously stimulating innovation.

The minimum anticipated biological effect level (MABEL) for selection of first human dose in clinical trials with monoclonal antibodies

Dose selection for first-in-human (FIH) clinical trials with monoclonal antibodies (mAbs) is based on specifically designed preclinical pharmacology and toxicology studies, mechanistic ex vivo/in vitro investigations with human and animal cells and pharmacokinetic/pharmacodynamic (PK/PD) modeling approaches and requires a thorough understanding of the biology of the target and the relative binding and pharmacological activity of the mAb in animals and humans. These investigations provide the essential information required for the selection of a safe starting dose and escalation for FIH trials based on toxicology and pharmacology data and the minimal anticipated biological effect level (MABEL) by integrating all available in vivo and in vitro data. In this review, strategies for estimation of the MABEL for mAbs specific for both membrane and soluble targets are presented and the scientific and regulatory challenges highlighted.

Practical anticipation of human efficacious doses and pharmacokinetics using in vitro and preclinical in vivo data

Accurate predictions of human pharmacokinetic and pharmacodynamic (PK/PD) profiles are critical in early drug development, as safe, efficacious, and "developable" dosing regimens of promising compounds have to be identified. While advantages of successful integration of preclinical PK/PD data in the "anticipation" of human doses (AHD) have been recognized, pharmaceutical scientists have faced difficulties with practical implementation, especially for PK/PD profile projections of compounds with challenging absorption, distribution, metabolism, excretion and formulation properties. In this article, practical projection approaches for formulation-dependent human PK/PD parameters and profiles of Biopharmaceutics Classification System classes I-IV drugs based on preclinical data are described. Case examples for "AHD" demonstrate the utility of preclinical and clinical PK/PD modeling for formulation risk identification, lead candidate differentiation, and prediction of clinical outcome. The application of allometric scaling methods and physiologically based pharmacokinetic approaches for clearance or volume of distribution projections is described using GastroPlus. Methods to enhance prediction confidence such as in vitro-in vivo extrapolations in clearance predictions using in vitro microsomal data are discussed. Examples for integration of clinical PK/PD and formulation data from frontrunner compounds via "reverse pharmacology strategies" that minimize uncertainty with PK/PD predictions are included. The use of integrated softwares such as GastroPlus in combination with established PK projection methods allow the projection of formulation-dependent preclinical and human PK/PD profiles required for compound differentiation and development risk assessments.

To scale or not to scale: the principles of dose extrapolation

The principles of inter-species dose extrapolation are poorly understood and applied. We provide an overview of the principles underlying dose scaling for size and dose adjustment for size-independent differences. Scaling of a dose is required in three main situations: the anticipation of first-in-human doses for clinical trials, dose extrapolation in veterinary practice and dose extrapolation for experimental purposes. Each of these situations is discussed. Allometric scaling of drug doses is commonly used for practical reasons, but can be more accurate when one takes into account species differences in pharmacokinetic parameters (clearance, volume of distribution). Simple scaling of drug doses can be misleading for some drugs; correction for protein binding, physicochemical properties of the drug or species differences in physiological time can improve scaling. However, differences in drug transport and metabolism, and in the dose-response relationship, can override the effect of size alone. For this reason, a range of modelling approaches have been developed, which combine in silico simulations with data obtained in vitro and/or in vivo. Drugs that are unlikely to be amenable to simple allometric scaling of their clearance or dose include drugs that are highly protein-bound, drugs that undergo extensive metabolism and active transport, drugs that undergo significant biliary excretion (MW > 500, ampiphilic, conjugated), drugs whose targets are subject to inter-species differences in expression, affinity and distribution and drugs that undergo extensive renal secretion. In addition to inter-species dose extrapolation, we provide an overview of dose extrapolation within species, discussing drug dosing in paediatrics and in the elderly.