Trial Design and Statistical Considerations on the Assessment of Pharmacodynamic Similarity.

Pharmacodynamics (PD) similarity is an important component to support the claim of similarity between two drugs or devices. This article investigates the trial design and statistical considerations in the equivalence test of PD endpoints. Using bone resorption marker CTX as a case study, the relationship between the PD readouts and drug potency was explored to evaluate the sensitivity of the PD endpoint and guide equivalence margin selection. For PD data that have high baseline variability, one conventional similarity assessment method was to apply baseline-normalization followed by the standard bioequivalence (BE) test (Lancet Haematol. 4:e350-61, 2017, Ann Rheum Dis. 2017). This study showcased the drawbacks of the conventional method for PD data that were close to inhibition saturation, as the baseline-normalization significantly skewed the distribution of the PD data toward non-log-normal. In such cases, the standard BE test can produce an inflated type I error. Alternatively, ANCOVA, when applied to the un-normalized PD data with the baseline as a covariate, produced a satisfactory type I error with sufficient power. Therefore, ANCOVA was recommended for equivalence test of PD markers that has a saturated inhibition profile and high variability at baseline. Moreover, the relationship between PD readouts and drug potency was used to explore the sensitivity of the PD endpoint and it could help justify the equivalence margins, since the standard 80% to 125% BE margin often does not apply to PD. Finally, a decision tree was proposed to help guide the design of the PD equivalence study in the choice of PD endpoints and statistical methods.

Therapeutic Drug Monitoring of Biologics for Inflammatory Bowel Disease: An Answer to Optimized Treatment?

Therapeutic drug monitoring (TDM), or the measurement of drug concentrations in blood and antidrug antibodies, for biologic therapies used to treat inflammatory bowel disease (IBD) is an area of growing interest within the IBD community. When there is a definable relationship between drug concentration and clinical effect, blood concentration of biologics (and antidrug antibodies assessment) could be used to predict patient response and to titrate the biologics to maximize therapeutic benefit. This dose individualization has been proven to be more efficacious and cost-effective than empiric dose adjustment and can better guide therapeutic decisions regarding therapy withdrawal or switch. Appropriate implementation and interpretation of drug concentration measurement in TDM are essential to ensure full clinical benefit. Factors that need to be considered include sources of variability, timing of blood sampling, dosing history, analytical performance, immunogenicity, comedications, and clinical status of the patients. Desired target concentrations for biologics used in IBD have not been clearly determined yet. Published concentration thresholds differed widely for a given biologic, indicating a lack of consistent information. Factors other than drug concentration that may contribute to the dose-response variation are largely missing in the current TDM setting. A target range is likely preferable to a single value for TDM of biologics in IBD, and additional prospective research needs to be conducted in order to establish these ranges. Moving forward, TDM may be combined with pharmacodynamic end points and modeling and simulation tools for improved therapeutic benefit in IBD.

Therapeutic protein-drug interactions: plausible mechanisms and assessment strategies.

INTRODUCTION: Over the last three decades, therapeutic proteins have played an increasingly important role in pharmacotherapy. Owing to an expected significant increase in the coadministration of biotherapeutics with established pharmacotherapy regimens or even with other biotherapeutic agents, there is an increasing likelihood for the occurrence of clinically relevant drug interactions, so called therapeutic protein-drug interactions (TP-DIs). Areas covered: Our current understanding of TP-DIs and recent collaborations among industry, academia and regulatory agencies are reviewed in this article. Although most of the observed TP-DIs are mediated by disease states, immune status, and/or target physiology, TP-DI assessments are still done empirically. Plausible mechanisms of major TP-DIs involving therapeutic proteins (primarily monoclonal antibodies), either as victims or as perpetrators, are proposed, with mechanism-based strategies and assessment approaches to better evaluate their propensity are recommended. Expert opinion: Our current understanding of the mechanisms of TP-DIs is in its infancy. Much of the basic research needs to be conducted to verify existing TP-DI hypotheses or help predict and manage potential ones, whose efforts are not considered trivial and may be better achieved through close collaborations among scientists from academia, industry, and regulatory agencies.

Therapeutic protein drug-drug interactions: navigating the knowledge gaps-highlights from the 2012 AAPS NBC Roundtable and IQ Consortium/FDA workshop.

The investigation of therapeutic protein drug-drug interactions has proven to be challenging. In May 2012, a roundtable was held at the American Association of Pharmaceutical Scientists National Biotechnology Conference to discuss the challenges of preclinical assessment and in vitro to in vivo extrapolation of these interactions. Several weeks later, a 2-day workshop co-sponsored by the U.S. Food and Drug Administration and the International Consortium for Innovation and Quality in Pharmaceutical Development was held to facilitate better understanding of the current science, investigative approaches and knowledge gaps in this field. Both meetings focused primarily on drug interactions involving therapeutic proteins that are pro-inflammatory cytokines or cytokine modulators. In this meeting synopsis, we provide highlights from both meetings and summarize observations and recommendations that were developed to reflect the current state of the art thinking, including a four-step risk assessment that could be used to determine the need (or not) for a dedicated clinical pharmacokinetic interaction study.

AAPS workshop report: strategies to address therapeutic protein-drug interactions during clinical development.

Therapeutic proteins (TPs) are increasingly combined with small molecules and/or with other TPs. However preclinical tools and in vitro test systems for assessing drug interaction potential of TPs such as monoclonal antibodies, cytokines and cytokine modulators are limited. Published data suggests that clinically relevant TP-drug interactions (TP-DI) are likely from overlap in mechanisms of action, alteration in target and/or drug-disease interaction. Clinical drug interaction studies are not routinely conducted for TPs because of the logistical constraints in study design to address pharmacokinetic (PK)- and pharmacodynamic (PD)-based interactions. Different pharmaceutical companies have developed their respective question- and/or risk-based approaches for TP-DI based on the TP mechanism of action as well as patient population. During the workshop both company strategies and regulatory perspectives were discussed in depth using case studies; knowledge gaps and best practices were subsequently identified and discussed. Understanding the functional role of target, target expression and their downstream consequences were identified as important for assessing the potential for a TP-DI. Therefore, a question-and/or risk-based approach based upon the mechanism of action and patient population was proposed as a reasonable TP-DI strategy. This field continues to evolve as companies generate additional preclinical and clinical data to improve their understanding of possible mechanisms for drug interactions. Regulatory agencies are in the process of updating their recommendations to sponsors regarding the conduct of in vitro and in vivo interaction studies for new drug applications (NDAs) and biologics license applications (BLAs).

Informative dropout modeling of longitudinal ordered categorical data and model validation: application to exposure-response modeling of physician's global assessment score for ustekinumab in patients with psoriasis.

The physician's global assessment (PGA) score is a 6-point measure of psoriasis severity that is widely used in clinical trials to assess response to psoriasis treatment. The objective of this study was to perform exposure-response modeling using the PGA score as a pharmacodynamic endpoint following treatment with ustekinumab in patients with moderate-to-severe psoriasis who participated in two Phase 3 studies (PHOENIX 1 and PHOENIX 2). Patients were randomly assigned to receive ustekinumab 45 or 90 mg or placebo, followed by active treatment or placebo crossover to ustekinumab, dose intensification or randomized withdrawal and long-term extension periods. A novel joint longitudinal-dropout model was developed from serum ustekinumab concentrations, PGA scores, and patient dropout information. The exposure-response component employed a semi-mechanistic drug model, integrated with disease progression and placebo effect under the mixed-effect logistic regression framework. This allowed potential tolerance to be investigated with a mechanistic approach. The dropout component of the joint model allowed the examination of its potential influence on the exposure-response relationship. The flexible Weibull dropout hazard function was used. Visual predictive check of the joint longitudinal-dropout model required special handling, and a conditional approach was proposed. The conditional approach was extended to external model validation. Finally, appropriate interpretation of model validation is discussed. This longitudinal-dropout model can serve as a basis to support future alternative dosing regimens for ustekinumab in patients with moderate-to-severe plaque psoriasis.

Risk-based strategy for the assessment of pharmacokinetic drug-drug interactions for therapeutic monoclonal antibodies.

Biological agents are used to treat a variety of diseases in many therapeutic areas, including oncology, rheumatology, gastroenterology, dermatology, respiratory disease, hormone deficiency and infection. While biologics constitute many of the recently approved new therapies, clinical research of drug-drug interactions with biologics has been scant. This review presents a risk-based assessment strategy for evaluating drug-drug interactions with monoclonal antibodies, a predominant class of therapeutic biologics. The key parameters of this strategy are described here, as well as suggested studies that should be considered as part of the overall drug development process for therapeutic biologics.

Pharmacokinetic drug-drug interaction potentials for therapeutic monoclonal antibodies: reality check.

A formal assessment of the drug-drug interaction potential of any investigational drug product often requires multiple metabolic and pharmacokinetic evaluations. In contrast to a small-molecule drug, investigating the drug-drug interaction potential of a monoclonal antibody is inherently complicated. High molecular weight monoclonal antibodies are often genetically engineered to demonstrate strong specificity for a particular human antigen target. Consequently, monoclonal antibodies usually have few clinically relevant animal models--other than nonhuman primates--in which to conduct appropriate nonclinical studies. Likewise, clinical drug-drug interaction studies of monoclonal antibodies with long elimination half-lives pose definite operational challenges as conventional crossover studies with adequate washout periods are difficult to conduct. Furthermore, the current regulatory guidance on the design and conduct of in vitro and in vivo drug-drug interaction studies applies more readily to small-molecule drugs than protein-based biologics. Nevertheless, a certain amount of clinically useful information has begun to emerge from the published literature on drug-drug interaction potentials of therapeutic monoclonal antibodies. This article provides a systematic review of the current literature and offers some practical considerations for the design and conduct of pharmacokinetic drug-drug interaction assessments involving novel monoclonal antibodies. Ideally, these evaluations should be performed throughout all stages of drug development. In particular, pharmacokinetic interaction studies with any marketed drugs that are likely to be coadministered with the monoclonal antibody will yield the most clinically useful information for practitioners and patients alike.

Population pharmacokinetic analysis and simulation of the time-concentration profile of etanercept in pediatric patients with juvenile rheumatoid arthritis.

This study was performed to estimate the population pharmacokinetic (PK) parameters of etanercept in pediatric juvenile rheumatoid arthritis (JRA) patients and to compare the steady-state time-concentration profiles between etanercept 0.8-mg/kg once-weekly and 0.4-mg/kg twice-weekly subcutaneous (SC) regimens by clinical trial simulation. To this end, mixed-effect analysis (NONMEM, Version 5.1) was performed using the etanercept PK database consisting of 69 JRA patients (4-17 years). Based on the population PK parameters obtained herein, a Monte Carlo clinical trial simulation experiment was conducted to compare the PK profiles in 200 virtual JRA patients who randomly received either etanercept 0.4 mg/kg SC twice weekly or 0.8 mg/kg once weekly for 12 weeks. The following population PK model could adequately describe etanercept PK profiles for twice-weekly SC dosing of 0.4 mg/kg: CL/F (L/h)=0.0576 (female) or 0.0772 (male) x (body surface area in m2/1.071)1.41, V/F(L)=7.88 x (body weight in kg/30.8). The means +/- standard deviations of simulated trough concentrations for 0.8-mg/kg once-weekly and 0.4-mg/kg twice-weekly dosing regimens were 1.58 +/- 1.07 mg/L and 1.92 +/- 1.09 mg/L, respectively. Peaks during 0.8-mg/kg once-weekly dosing (2.92 +/- 1.41 mg/L) were only 11% higher than during 0.4 mg/kg twice-weekly dosing (2.62 +/- 1.23 mg/L). In conclusion, the clinical trial simulation confirmed that 0.8-mg/kg once-weekly and 0.4-mg/kg twice-weekly SC regimens of etanercept are expected to yield overlapping steady-state time-concentration profiles, leading to equivalent clinical outcomes. This has been the basis of the recent Food and Drug Administration approval of the 0.8-mg/kg once-weekly regimen in pediatric patients with JRA.