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Upadacitinib, a selective Janus kinase inhibitor, is the first orally administered therapy approved for the treatment of Crohn's disease (CD). This work characterized the pharmacokinetics of upadacitinib in CD patients and evaluated the relationships between upadacitinib steady-state plasma exposures and efficacy as well as safety parameters during the 12-week induction and the 52-week maintenance periods, to provide dosing recommendations for the treatment of CD. Upadacitinib pharmacokinetics in CD patients administered the extended-release formulation were consistent with patient populations in other approved indications. None of the evaluated CD-specific patient characteristics (e.g., disease location and prior gastrointestinal surgeries) had a meaningful impact on upadacitinib pharmacokinetics. Exposure-response analyses during 12-week induction treatment showed that response across all evaluated efficacy end points were approaching a plateau at median plasma exposures associated with 45 mg QD. Analyses for the maintenance period demonstrated that 30 mg QD is predicted to provide an additional 8% to 10% benefit for endoscopic response and endoscopic remission compared with 15 mg QD in patients who failed biologics. The analyses for safety showed a statistically significant relationship between increasing upadacitinib plasma exposures and the percentage of patients experiencing >2 g/dL decrease in hemoglobin from Baseline during induction and showed shallow relationships for serious infections and herpes zoster during the maintenance period. These results demonstrated adequate absorption of the extended-release formulation of upadacitinib in CD patients. The exposure-response analyses confirmed that 45 mg QD dose maximized efficacy as induction treatment and supported the selection of 15 mg QD or 30 mg QD as the maintenance doses., (© 2024 AbbVie Inc. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Cedirogant is an inverse agonist of retinoic acid-related orphan receptor gamma thymus developed for the treatment of chronic plaque psoriasis. Cedirogant induces cytochrome P450 (CYP) 3A4 while inhibiting P-glycoprotein (P-gp), breast cancer resistance protein (BCRP), organic anion transporting polypeptide (OATP) 1B1, and OATP1B3 in vitro. Static drug-drug interactions (DDIs) predictions suggested possible clinical induction of CYP3A4, and inhibition of P-gp, BCRP, and OATP1B1, leading to challenges in interpreting DDI studies between cedirogant and substrates of CYP3A, P-gp, BCRP, and OATP1B1/3. Here the effects of cedirogant on the pharmacokinetics of two statin drugs were investigated in healthy participants. Coproporphyrin-I (CP-I), a selective endogenous OATP1B biomarker, was used to assess the impact of cedirogant on OATP1B. Cedirogant (375 mg once daily) increased rosuvastatin maximum plasma concentration (C max ) and area under the plasma concentration curve (AUC tau ) by 141% and 55%, respectively when co-administered, whereas atorvastatin C max increased by 40% with no effect on its AUC tau compared with administration of rosuvastatin/atorvastatin alone. Cedirogant did not increase CP-I exposures, indicating no clinical OATP1B inhibition. The increased rosuvastatin exposure and minimal change in atorvastatin exposure with co-administration of cedirogant is attributed to BCRP inhibition and interplay between P-gp/BCRP inhibition and CYP3A induction, respectively. Correlation analysis with data from two investigational drugs (glecaprevir and flubentylosin) demonstrated that OATP1B1 R-value of > 1.5 and [C max,u ]/[OATP1B1 IC 50 ] of > 0.1 are associated with > 1.25-fold increase in CP-I C max ratio. This demonstrates the utility of CP-I in disentangling mechanisms underlying a complex DDI involving multiple transporters and enzymes and proposes refined criteria for static OATP1B inhibition predictions., (© 2024 AbbVie Inc. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Physiologically-based pharmacokinetic (PBPK) modeling offers a viable approach to predict induction drug-drug interactions (DDIs) with the potential to streamline or reduce clinical trial burden if predictions can be made with sufficient confidence. In the current work, the ability to predict the effect of rifampin, a well-characterized strong CYP3A4 inducer, on 20 CYP3A probes with publicly available PBPK models (often developed using a workflow with optimization following a strong inhibitor DDI study to gain confidence in fraction metabolized by CYP3A4, f m,CYP3A4 , and fraction available after intestinal metabolism, Fg), was assessed. Substrates with a range of f m,CYP3A4 (0.086-1.0), Fg (0.11-1.0) and hepatic availability (0.09-0.96) were included. Predictions were most often accurate for compounds that are not P-gp substrates or that are P-gp substrates but that have high permeability. Case studies for three challenging DDI predictions (i.e., for eliglustat, tofacitinib, and ribociclib) are presented. Along with parameter sensitivity analysis to understand key parameters impacting DDI simulations, alternative model structures should be considered, for example, a mechanistic absorption model instead of a first-order absorption model might be more appropriate for a P-gp substrate with low permeability. Any mechanisms pertinent to the CYP3A substrate that rifampin might impact (e.g., induction of other enzymes or P-gp) should be considered for inclusion in the model. PBPK modeling was shown to be an effective tool to predict induction DDIs with rifampin for CYP3A substrates with limited mechanistic complications, increasing confidence in the rifampin model. While this analysis focused on rifampin, the learnings may apply to other inducers., (© 2024 The Author(s). Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Juvenile idiopathic arthritis (JIA) is the most prevalent pediatric rheumatic disease. While disease-modifying antirheumatic drugs (DMARDs), especially biologics, have greatly transformed the management of JIA, there remain some unmet medical needs that require new treatment options. The objective of this work was to describe and apply a modeling and simulation approach to extrapolate upadacitinib efficacy from the adult diseases, rheumatoid arthritis (RA) and psoriatic arthritis (PsA), to their respective pediatric diseases, polyarticular course JIA (pcJIA), and juvenile PsA (JPsA). A population pharmacokinetic model characterized upadacitinib pharmacokinetics in pediatric patients using data from two phase I studies in pediatric patients with pcJIA (N = 51) or atopic dermatitis (N = 33). Efficacy simulations were conducted using previously developed exposure-response models in adults with RA and PsA. Real-world pcJIA and JPsA patient databases were leveraged to construct representative patient profiles for the targeted population. Following administration of the proposed weight-based dosing regimen, the model-predicted median upadacitinib plasma exposures in pediatric patients were within 20% of those in adult RA and PsA patients receiving the approved adult regimen. Simulations demonstrate that upadacitinib efficacy in pcJIA and JPsA is predicted to be non-inferior to that in adults with RA or PsA, respectively. The results of this work enabled recent approvals of upadacitinib for the treatment of polyarticular JIA and JPsA in the United States. Upadacitinib safety in pediatrics is being further evaluated in ongoing clinical trials., (© 2024 AbbVie Inc. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Data from phase IIb/III and phase III studies were used to characterize the population pharmacokinetics of risankizumab and its exposure-response relationships for efficacy and safety in ulcerative colitis (UC) patients. A two-compartment model with first-order absorption and elimination accurately described risankizumab pharmacokinetics. Although certain covariates, namely, body weight, serum albumin, fecal calprotectin, sex, corticosteroid use, advanced therapy inadequate response, and pancolitis, were statistically correlated with risankizumab clearance, their impact on exposure was not clinically meaningful for efficacy or safety. Phase II exposure-response analyses demonstrated that the 1,200 mg intravenous (IV) induction dose at Weeks 0, 4, and 8 achieved near maximal response for all efficacy end points, with suboptimal efficacy from the 600 mg and little added benefit from the 1,800 mg regimens, justifying 1,200 mg IV as the induction dose in the phase III study. Phase III exposure-response analyses for efficacy during induction showed statistically significant exposure-response relationships at Week 12 following 1,200 mg IV at Weeks 0, 4, and 8, in line with phase IIb results. Exposure-response analyses for maintenance demonstrated modest improvement in Week 52 efficacy when increasing the subcutaneous dose from 180 mg to 360 mg with largely overlapping confidence intervals. Exposure-response analyses for safety indicated no apparent exposure-dependent safety events over the induction or maintenance treatment. Based on these results, the recommended dosing regimen for risankizumab in UC patients is 1,200 mg IV at Weeks 0, 4, and 8, followed by 180 mg or 360 mg subcutaneously at Week 12 and every 8 weeks thereafter., (© 2024 AbbVie Inc. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The landscape of oncology drug development has witnessed remarkable advancements over the last few decades, significantly improving clinical outcomes and quality of life for patients with cancer. Project Optimus, introduced by the U.S. Food and Drug Administration, stands as a groundbreaking endeavor to reform dose selection of oncology drugs, presenting both opportunities and challenges for the field. To address complex dose optimization challenges, an Oncology Dose Optimization IQ Working Group was created to characterize current practices, provide recommendations for improvement, develop a clinical toolkit, and engage Health Authorities. Historically, dose selection for cytotoxic chemotherapeutics has focused on the maximum tolerated dose, a paradigm that is less relevant for targeted therapies and new treatment modalities. A survey conducted by this group gathered insights from member companies regarding industry practices in oncology dose optimization. Given oncology drug development is a complex effort with multidimensional optimization and high failure rates due to lack of clinically relevant efficacy, this Working Group advocates for a case-by-case approach to inform the timing, specific quantitative targets, and strategies for dose optimization, depending on factors such as disease characteristics, patient population, mechanism of action, including associated resistance mechanisms, and therapeutic index. This white paper highlights the evolving nature of oncology dose optimization, the impact of Project Optimus, and the need for a tailored and evidence-based approach to optimize oncology drug dosing regimens effectively., (© 2024 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

A review of the use of microdoses and isotopic microtracers for clinical intravenous pharmacokinetic (i.v. PK) data provision is presented. The extent of application of the varied approaches available and the relative merits of each are highlighted with the aim of assisting practitioners in making informed decisions on the most scientifically appropriate design to adopt for any given new drug in development. It is envisaged that significant efficiencies will be realized as i.v. PK data in humans becomes more routinely available for suitable assets in early development, than has been the case prior to the last decade., (© 2023 GSK Research and Development Ltd. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The intent of this perspective is to share the recommendations of the International Consortium for Innovation and Quality in Pharmaceutical Development Metabolite Bioanalysis Working Group on the fit-for-purpose metabolite bioanalysis in support of drug development and registration. This report summarizes the considerations for the trigger, timing, and rigor of bioanalysis in the various assessments to address unique challenges due to metabolites, with respect to efficacy and safety, which may arise during drug development from investigational new drug (IND) enabling studies, and phase I, phase II, and phase III clinical trials to regulatory submission. The recommended approaches ensure that important drug metabolites are identified in a timely manner and properly characterized for efficient drug development., (© 2023 Novartis. AbbVie Inc. Incyte Corporation et al. Clinical Pharmacology & Therapeutics © 2023 American Society for Clinical Pharmacology and Therapeutics.)

Recent breakthroughs in artificial intelligence (AI) and machine learning (ML) have ushered in a new era of possibilities across various scientific domains. One area where these advancements hold significant promise is model-informed drug discovery and development (MID3). To foster a wider adoption and acceptance of these advanced algorithms, the Innovation and Quality (IQ) Consortium initiated the AI/ML working group in 2021 with the aim of promoting their acceptance among the broader scientific community as well as by regulatory agencies. By drawing insights from workshops organized by the working group and attended by key stakeholders across the biopharma industry, academia, and regulatory agencies, this white paper provides a perspective from the IQ Consortium. The range of applications covered in this white paper encompass the following thematic topics: (i) AI/ML-enabled Analytics for Pharmacometrics and Quantitative Systems Pharmacology (QSP) Workflows; (ii) Explainable Artificial Intelligence and its Applications in Disease Progression Modeling; (iii) Natural Language Processing (NLP) in Quantitative Pharmacology Modeling; and (iv) AI/ML Utilization in Drug Discovery. Additionally, the paper offers a set of best practices to ensure an effective and responsible use of AI, including considering the context of use, explainability and generalizability of models, and having human-in-the-loop. We believe that embracing the transformative power of AI in quantitative modeling while adopting a set of good practices can unlock new opportunities for innovation, increase efficiency, and ultimately bring benefits to patients., (© 2023 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

CAR-T therapies have shown remarkable efficacy against hematological malignancies in the clinic over the last decade and new studies indicate that progress is being made to use these novel therapies to target solid tumors as well as treat autoimmune disease. Innovation in the field, including TCR-T, allogeneic or "off the shelf" CAR-T, and autoantigen/armored CAR-Ts are likely to increase the efficacy and applications of these therapies. The unique aspects of these cell-based therapeutics; patient-derived cells, intracellular expression, in vivo expansion, and phenotypic changes provide unique bioanalytical challenges to develop pharmacokinetic and immunogenicity assessments. The International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) Translational and ADME Sciences Leadership Group (TALG) has brought together a group of industry experts to discuss and consider these challenges. In this white paper, we present the IQ consortium perspective on the best practices and considerations for bioanalytical and immunogenicity aspects toward the optimal development of CAR-T and TCR-T cell therapies., (© 2023 The Authors. Clinical Pharmacology & Therapeutics © 2023 American Society for Clinical Pharmacology and Therapeutics.)

Drug-drug interactions (DDIs) involving hepatic organic anion transporting polypeptides 1B1/1B3 (OATP1B) can be substantial, however, challenges remain for predicting interaction risk. Emerging evidence suggests that endogenous biomarkers, particularly coproporphyrin-I (CP-I), can be used to assess in vivo OATP1B activity. The present work under the International Consortium for Innovation and Quality in Pharmaceutical Development was aimed primarily at assessing CP-I as a biomarker for informing OATP1B DDI risk. Literature and unpublished CP-I data along with pertinent in vitro and clinical DDI information were collected to identify DDIs primarily involving OATP1B inhibition and assess the relationship between OATP1B substrate drug and CP-I exposure changes. Static models to predict changes in exposure of CP-I, as a selective OATP1B substrate, were also evaluated. Significant correlations were observed between CP-I area under the curve ratio (AUCR) or maximum concentration ratio (C max R) and AUCR of substrate drugs. In general, the CP-I C max R was equal to or greater than the CP-I AUCR. CP-I C max R < 1.25 was associated with absence of OATP1B-mediated DDIs (AUCR < 1.25) with no false negative predictions. CP-I C max R < 2 was associated with weak OATP1B-mediated DDIs (AUCR < 2). A correlation was identified between CP-I exposure changes and OATP1B1 static DDI predictions. Recommendations for collecting and interpreting CP-I data are discussed, including a decision tree for guiding DDI risk assessment. In conclusion, measurement of CP-I is recommended to inform OATP1B inhibition potential. The current analysis identified changes in CP-I exposure that may be used to prioritize, delay, or replace clinical DDI studies., (© 2023 The Authors. Clinical Pharmacology & Therapeutics © 2023 American Society for Clinical Pharmacology and Therapeutics.)

With the promise of a potentially "single dose curative" paradigm, CAR-T cell therapies have brought a paradigm shift in the treatment and management of hematological malignancies. Both CAR-T and TCR-T cell therapies have also made great progress toward the successful treatment of solid tumor indications. The field is rapidly evolving with recent advancements including the clinical development of "off-the-shelf" allogeneic CAR-T therapies that can overcome the long and difficult "vein-to-vein" wait time seen with autologous CAR-T therapies. There are unique clinical pharmacology, pharmacometric, bioanalytical, and immunogenicity considerations and challenges in the development of these CAR-T and TCR-T cell therapies. Hence, to help accelerate the development of these life-saving therapies for the patients with cancer, experts in this field came together under the umbrella of International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) to form a joint working group between the Clinical Pharmacology Leadership Group (CPLG) and the Translational and ADME Sciences Leadership Group (TALG). In this white paper, we present the IQ consortium perspective on the best practices and considerations for clinical pharmacology and pharmacometric aspects toward the optimal development of CAR-T and TCR-T cell therapies., (© 2023 Amgen Inc and The Authors. Clinical Pharmacology & Therapeutics © 2023 American Society for Clinical Pharmacology and Therapeutics.)

Disease progression modeling (DPM) represents an important model-informed drug development framework. The scientific communities support the use of DPM to accelerate and increase efficiency in drug development. This article summarizes International Consortium for Innovation & Quality (IQ) in Pharmaceutical Development mediated survey conducted across multiple biopharmaceutical companies on challenges and opportunities for DPM. Additionally, this summary highlights the viewpoints of IQ from the 2021 workshop hosted by the US Food and Drug Administration (FDA). Sixteen pharmaceutical companies participated in the IQ survey with 36 main questions. The types of questions included single/multiple choice, dichotomous, rank questions, and open-ended or free text. The key results show that DPM has different representation, it encompasses natural disease history, placebo response, standard of care as background therapy, and can even be interpreted as pharmacokinetic/pharmacodynamic modeling. The most common reasons for not implementing DPM as frequently seem to be difficulties in internal cross-functional alignment, lack of knowledge of disease/data, and time constraints. If successfully implemented, DPM can have an impact on dose selection, reduction of sample size, trial read-out support, patient selection/stratification, and supportive evidence for regulatory interactions. The key success factors and key challenges of disease progression models were highlighted in the survey and about 24 case studies across different therapeutic areas were submitted from various survey sponsors. Although DPM is still evolving, its current impact is limited but promising. The success of such models in the future will depend on collaboration, advanced analytics, availability of and access to relevant and adequate-quality data, collaborative regulatory guidance, and published examples of impact., (© 2023 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Typically, therapeutic proteins (TPs) have a low risk for eliciting meaningful drug interactions (DIs). However, there are select instances where TP drug interactions (TP-DIs) of clinical concern can occur. This white paper discusses the various types of TP-DIs involving mechanisms such as changes in disease state, target-mediated drug disposition, neonatal Fc receptor (FcRn), or antidrug antibodies formation. The nature of TP drug interaction being investigated should determine whether the examination is conducted as a standalone TP-DI study in healthy participants, in patients, or assessed via population pharmacokinetic analysis. DIs involving antibody-drug conjugates are discussed briefly, but the primary focus here will be DIs involving cytokine modulation. Cytokine modulation can occur directly by certain TPs, or indirectly due to moderate to severe inflammation, infection, or injury. Disease states that have been shown to result in indirect disease-DIs that are clinically meaningful have been listed (i.e., typically a twofold change in the systemic exposure of a coadministered sensitive cytochrome P450 substrate drug). Type of disease and severity of inflammation should be the primary drivers for risk assessment for disease-DIs. While more clinical inflammatory marker data needs to be collected, the use of two or more clinical inflammatory markers (such as C-reactive protein, albumin, or interleukin 6) may help broadly categorize whether the predicted magnitude of inflammatory disease-DI risk is negligible, weak, or moderate to strong. Based on current knowledge, clinical DI studies are not necessary for all TPs, and should no longer be conducted in certain disease patient populations such as psoriasis, which do not have sufficient systemic inflammation to cause a meaningful indirect disease-DI., (© 2022 The Authors. Clinical Pharmacology & Therapeutics © 2022 American Society for Clinical Pharmacology and Therapeutics.)

Legislative and technological advancements over the past decade have given rise to the proliferation of healthcare data generated from routine clinical practice, often referred to as real-world data (RWD). These data have piqued the interest of healthcare stakeholders due to their potential utility in generating evidence to support clinical and regulatory decision making. In the oncology setting, studies leveraging RWD offer distinct advantages that are complementary to randomized controlled trials (RCTs). They also permit the conduct of investigations that may not be possible through prospective designs due to ethics or feasibility. Despite its promise, the use of RWD for the generation of clinical evidence remains controversial due to concerns of unmeasured confounding and other sources of bias that must be carefully addressed in the study design and analysis. To facilitate a better understanding of when RWD can provide reliable conclusions on drug effectiveness, we seek to conduct 10 RWD-based studies that emulate RCTs in oncology using a systematic, protocol-driven approach described herein. Results of this investigation will help inform clinical, scientific, and regulatory stakeholders on the applications of RWD in the context of product labeling expansion, drug safety, and comparative effectiveness in oncology., (© 2022 Aetion, Inc. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The population pharmacokinetics (PK) of risankizumab and exposure-response relationships for efficacy and safety in patients with Crohn's disease (CD) were characterized using data from phase II and III studies to support dosing regimen selection. A two-compartment model with first-order absorption and first-order elimination adequately described risankizumab PK. Covariates including sex, baseline fecal calprotectin, corticosteroid use, baseline creatinine clearance, body weight, and baseline albumin were statistically correlated with risankizumab clearance, but their impact on exposure was not clinically relevant for efficacy or safety. Exposure-response analyses showed that exposures associated with the 600 mg intravenous (i.v.) induction dose at Weeks 0, 4, and 8 achieved a near maximal response for all efficacy end points evaluated, with negligible added benefit from the 1,200 mg i.v. regimen. By Week 52 of the maintenance treatment, trends of higher responses were observed for the exposure range associated with the 360 mg subcutaneous (s.c.) every-8-weeks (Q8W) regimen for most of the evaluated efficacy end points, particularly for the more stringent end points, such as endoscopic remission and ulcer-free endoscopy. Exposure-response analyses for safety did not identify any apparent relationship between exposure and safety. These results supported the final dose recommendation of 600 mg i.v. at Weeks 0, 4, and 8, followed by 360 mg s.c. at Week 12 and Q8W thereafter in patients with CD., (© 2022 AbbVie Inc. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The human absorption, distribution, metabolism, and excretion (hADME) study is the cornerstone of the clinical pharmacology package for small molecule drugs, providing comprehensive information on the rates and routes of disposition and elimination of drug-related material in humans through the use of 14 C-labeled drug. Significant changes have already been made in the design of the hADME study for many companies, but opportunity exists to continue to re-think both the design and timing of the hADME study in light of the potential offered by newer technologies, that enable flexibility in particular to reducing the magnitude of the radioactive dose used. This paper provides considerations on the variety of current strategies that exist across a number of pharmaceutical companies and on some of the ongoing debates around a potential move to the so called "human first/human only" approach, already adopted by at least one company. The paper also provides a framework for continuing the discussion in the application of further shifts in the paradigm., (© 2022 GSK & Roche, et al. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

This review presents a European Federation of Pharmaceutical Industries and Association/PreClinical Development Expert Group (EFPIA-PDEG) topic group consensus on a data-driven approach to harmonized contraception recommendations for clinical trial protocols and product labeling. There is no international agreement in pharmaceutical clinical trial protocols or product labeling on when/if female and/or male contraception is warranted and for how long after the last dose. This absence of consensus has resulted in different recommendations among regions. For most pharmaceuticals, contraception recommendations are generally based exclusively on nonclinical data and/or mechanism. For clinical trials, contraception is the default position and is maintained for women throughout clinical development, whereas appropriate information can justify removing male contraception. Conversely, contraception is only recommended in product labeling when warranted. A base case rationale is proposed for whether or not female and/or male contraception is/are warranted, using available genotoxicity and developmental toxicity data. Contraception is generally warranted for both male and female subjects treated with mutagenic pharmaceuticals. We propose as a starting point that contraception is not typically warranted when the margin is 10-fold or greater between clinical exposure at the maximum recommended human dose and exposure at the no observed adverse effect level (NOAEL) for purely aneugenic pharmaceuticals and for pharmaceuticals that induce fetal malformations or embryo-fetal lethality. Other factors are discussed, including contraception methods, pregnancy testing, drug clearance, options for managing the absence of a developmental toxicity NOAEL, drug-drug interactions, radiopharmaceuticals, and other drug modalities. Overall, we present a data-driven rationale that can serve as a basis for consistent contraception recommendations in clinical trials and in product labeling across regions., (© 2022 Pfizer Inc. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Ceftazidime-avibactam is a novel β-lactam/β-lactamase inhibitor combination developed to treat serious Gram-negative bacterial infections; approved indications include complicated urinary tract infection, complicated intra-abdominal infection, and hospital-acquired pneumonia including ventilator-associated pneumonia in patients ≥ 3 months old. Because of the predominantly renal clearance of ceftazidime and avibactam, dose adjustments (reductions) are required for patients with estimated creatinine clearance (CrCL) ≤ 50 mL/min. We describe the application of combined adult and pediatric population pharmacokinetic models in developing ceftazidime-avibactam dose recommendations for pediatric patients ≥ 2 to < 18 years old with body surface area-normalized CrCL ≤ 50 mL/min/1.73 m 2 , including moderate, severe, or very severe renal impairment, or end-stage renal disease requiring hemodialysis, and for patients ≥ 3 months to < 2 years old with mild, moderate, or severe renal impairment. Models included allometric scaling for all subjects and simulations (1,000 subjects per age group, renal function group, and indication) were performed nonparametrically using post hoc random effects. Doses were selected based on simulated pediatric patients achieving steady-state exposures similar to adults and high probability of target attainment (using a simultaneous joint target for both ceftazidime and avibactam). Because there were few children with renal impairment in the ceftazidime-avibactam clinical trials, selected pediatric doses were guided by extrapolation and matching of adult exposures associated with efficacy and within established safety margins. The recommended doses for pediatric patients with estimated CrCL ≤ 50 mL/min/1.73 m 2 use equivalent adjustments in dose quantity and/or administration interval (vs. the corresponding age group with normal renal function) as those for adults., (© 2022 AbbVie Inc and Pfizer Inc. Clinical Pharmacology & Therapeutics © 2022 American Society for Clinical Pharmacology and Therapeutics.)

As the scientific research community along with healthcare professionals and decision makers around the world fight tirelessly against the coronavirus disease 2019 (COVID-19) pandemic, the need for comparative effectiveness research (CER) on preventive and therapeutic interventions for COVID-19 is immense. Randomized controlled trials markedly under-represent the frail and complex patients seen in routine care, and they do not typically have data on long-term treatment effects. The increasing availability of electronic health records (EHRs) for clinical research offers the opportunity to generate timely real-world evidence reflective of routine care for optimal management of COVID-19. However, there are many potential threats to the validity of CER based on EHR data that are not originally generated for research purposes. To ensure unbiased and robust results, we need high-quality healthcare databases, rigorous study designs, and proper implementation of appropriate statistical methods. We aimed to describe opportunities and challenges in EHR-based CER for COVID-19-related questions and to introduce best practices in pharmacoepidemiology to minimize potential biases. We structured our discussion into the following topics: (1) study population identification based on exposure status; (2) ascertainment of outcomes; (3) common biases and potential solutions; and (iv) data operational challenges specific to COVID-19 CER using EHRs. We provide structured guidance for the proper conduct and appraisal of drug and vaccine effectiveness and safety research using EHR data for the pandemic. This paper is endorsed by the International Society for Pharmacoepidemiology (ISPE)., (© 2022 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Coadministration with acid-reducing agents (ARAs), including proton pump inhibitors (PPIs), histamine H 2 -receptor antagonists (H 2 blockers), and antacids has been demonstrated to reduce antiviral exposure and efficacy. Therefore, it is essential that US Food and Drug Administration (FDA) drug labels include recommendations to manage these drug-drug interactions (DDIs). This investigation analyzed information in FDA drug labels to manage DDIs between ARAs and antivirals approved from 1998 to 2019. To ascertain clinical adoption, we assessed whether FDA label recommendations were incorporated into current antiviral clinical practice guidelines. We identified 82 label recommendations for 43 antiviral approvals. Overall, 56.1% of recommendations were deemed clinically actionable, with the most common actionable management strategies being dose adjustment during coadministration (40.2%) and coadministration not recommended (9.8%). The sources informing DDI recommendations were clinical DDI studies (59.8%) and predictions of altered exposure (40.2%). Antivirals with low aqueous solubility were more likely to have label recommendations and were more commonly investigated using clinical DDI studies (P < 0.01). For recommendations informed by clinical DDI studies, changes in drug exposure were associated with actionable label recommendations (P < 0.01). The frequency of exposure changes in clinical DDI studies was similar across antiviral indications, but exposure changes were numerically higher for antacids (71.4%) relative to PPIs (42.9%) and H 2 blockers (28.6%). Of DDI pairs identified within drug labels, 76.8% were included in guidelines, and recommended management strategies were concordant in 90.5% of cases. Our findings demonstrate that current regulatory oversight mostly (but not completely) results in actionable label recommendations to manage DDIs for high-risk antivirals., (© 2022 The Authors. Clinical Pharmacology & Therapeutics © 2022 American Society for Clinical Pharmacology and Therapeutics.)

The International Consortium for Innovation and Quality (IQ) Physiologically Based Pharmacokinetic (PBPK) Modeling Induction Working Group (IWG) conducted a survey across participating companies around general strategies for PBPK modeling of induction, including experience with its utility to address various questions, regulatory interactions, and regulatory acceptance. The results highlight areas where PBPK modeling is used with high confidence and identifies opportunities where confidence is lower and further evaluation is needed. To enhance the survey results, the PBPK-IWG also collected case studies and analyzed recent literature examples where PBPK models were applied to predict CYP3A induction-mediated drug-drug interactions. PBPK modeling of induction has evolved and progressed significantly, proving to have great potential to accelerate drug discovery and development. With the aim of enabling optimal use for new molecular entities that are either substrates and/or inducers of CYP3A, the PBPK-IWG proposes initial workflows for PBPK application, discusses future trends, and identifies gaps that need to be addressed., (© 2021 The Authors. Clinical Pharmacology & Therapeutics © 2021 American Society for Clinical Pharmacology and Therapeutics.)

Antibody-drug conjugates (ADCs) represent a rapidly evolving area of drug development and hold significant promise. To date, nine ADCs have been approved by the US Food and Drug Administration (FDA). These conjugates combine the target specificity of monoclonal antibodies with the anticancer activity of small-molecule therapeutics (also referred to as payload). Due to the complex structure, three analytes, namely ADC conjugate, total antibody, and unconjugated payload, are typically quantified during drug development; however, the benefits of measuring all three analytes at later stages of clinical development are not clear. The cytotoxic payloads, upon release from the ADC, are considered to behave like small molecules. Given the relatively high potency and low systemic exposure of cytotoxic payloads, drug-drug interaction (DDI) considerations for ADCs might be different from traditional small molecule therapeutics. The International Consortium for Innovation and Quality in Pharmaceutical Development (IQ Consortium) convened an ADC working group to create an IQ ADC database that includes 26 ADCs with six unique payloads. The analysis of the ADC data in the IQ database, as well as nine approved ADCs, supports the strategy of pharmacokinetic characterization of all three analytes in early-phase development and progressively minimizing the number of analytes to be measured in the late-phase studies. The systemic concentrations of unconjugated payload are usually too low to serve as a DDI perpetrator; however, the potential for unconjugated payloads as a victim still exists. A data-driven and risk-based decision tree was developed to guide the assessment of a circulating payload as a victim of DDI., (© 2021 The Authors. Clinical Pharmacology & Therapeutics © 2021 American Society for Clinical Pharmacology and Therapeutics.)

The role of membrane transporters on pharmacokinetics (PKs), drug-drug interactions (DDIs), pharmacodynamics (PDs), and toxicity of drugs has been broadly recognized. However, our knowledge of modulation of transporter expression and/or function in the diseased patient population or specific populations, such as pediatrics or pregnancy, is still emerging. This white paper highlights recent advances in studying the changes in transporter expression and activity in various diseases (i.e., renal and hepatic impairment and cancer) and some specific populations (i.e., pediatrics and pregnancy) with the focus on clinical implications. Proposed alterations in transporter abundance and/or activity in diseased and specific populations are based on (i) quantitative transporter proteomic data and relative abundance in specific populations vs. healthy adults, (ii) clinical PKs, and emerging transporter biomarker and/or pharmacogenomic data, and (iii) physiologically-based pharmacokinetic modeling and simulation. The potential for altered PK, PD, and toxicity in these populations needs to be considered for drugs and their active metabolites in which transporter-mediated uptake/efflux is a major contributor to their absorption, distribution, and elimination pathways and/or associated DDI risk. In addition to best practices, this white paper discusses current challenges and knowledge gaps to study and quantitatively predict the effects of modulation in transporter activity in these populations, together with the perspectives from the International Transporter Consortium (ITC) on future directions., (© 2022 The Authors. Clinical Pharmacology & Therapeutics © 2022 American Society for Clinical Pharmacology and Therapeutics.)

Severe neutropenia is the major dose-liming toxicity of irinotecan-based chemotherapy. The objective was to assess to what extent a population pharmacokinetic/pharmacodynamic model including patient-specific demographic/clinical characteristics, individual pharmacokinetics, and absolute neutrophil counts (ANCs) can predict irinotecan-induced grade 4 neutropenia. A semimechanistic population pharmacokinetic/pharmacodynamic model was developed to describe neutrophil response over time in 197 patients with cancer receiving irinotecan. For covariate analysis, sex, race, age, pretreatment total bilirubin, and body surface area were evaluated to identify significant covariates on system-related parameters (mean transit time (MTT) and ɣ) and sensitivity to neutropenia effects of irinotecan and SN-38 (SLOPE). The model-based simulation was performed to assess the contribution of the identified covariates, individual pharmacokinetics, and baseline ANC alone or with incremental addition of weekly ANC up to 3 weeks on predicting irinotecan-induced grade 4 neutropenia. The time course of neutrophil response was described using the model assuming that irinotecan and SN-38 have toxic effects on bone marrow proliferating cells. Sex and pretreatment total bilirubin explained 10.5% of interindividual variability in MTT. No covariates were identified for SLOPE and γ. Incorporating sex and pretreatment total bilirubin (area under the receiver operating characteristic curve (AUC-ROC): 50%, 95% CI 50-50%) or with the addition of individual pharmacokinetics (AUC-ROC: 62%, 95% CI 53-71%) in the model did not result in accurate prediction of grade 4 neutropenia. However, incorporating ANC only at baseline and week 1 in the model achieved a good prediction (AUC-ROC: 78%, 95% CI 69-88%). These results demonstrate the potential applicability of a model-based approach to predict irinotecan-induced neutropenia, which ultimately allows for personalized intervention to maximize treatment outcomes., (© 2022 The Authors. Clinical Pharmacology & Therapeutics © 2022 American Society for Clinical Pharmacology and Therapeutics.)

Hypertension is a common bevacizumab-induced toxicity. No markers are available to predict patients at risk of developing hypertension. We hypothesized that genetic risk of essential hypertension, as measured by a blood pressure polygenic risk score (PRS), would be associated with risk of severe bevacizumab-induced hypertension. PRSs were calculated for 1,027 bevacizumab-treated patients of European descent with cancer from four clinical trials (Alliance for Clinical Trials in Oncology (Alliance) / Cancer and Leukemia Group B (CALGB) 80303, 40503, 90401, 40502) using summary systolic blood pressure (SBP) and diastolic blood pressure (DBP) genome-wide association results obtained from 757,601 individuals of European descent. The association between PRS and grade 3 bevacizumab-induced hypertension (Common Toxicity Criteria for Adverse Events version 3) in each trial was performed by multivariable logistic regression. Fixed-effect meta-analyses odds ratios (ORs) per standard deviation (SD) of the association of PRS (quantitative) and hypertension across trials were estimated by inverse-variance weighting. PRSs were additionally stratified into quintiles, with the bottom quintile as the referent group. The OR of the association between hypertension and each quintile vs. the referent group was determined by logistic regression. The most significant PRS (quantitative)-hypertension association included up to 67 single-nucleotide variants (SNPs) associated with SBP (P = 0.0077, OR per SD = 1.31, 95% confidence interval (CI), 1.07-1.60), and up to 53 SNPs associated with DBP (P = 0.0209, OR per SD = 1.27, 95% CI, 1.04-1.56). Patients in the top quintile had a higher risk of developing bevacizumab-induced hypertension compared with patients in the bottom quintile using SNPs associated with SBP (P = 4.75 × 10 -4 , OR = 3.72, 95% CI, 1.84-8.16) and DBP (P = 0.076, OR = 1.83, 95% CI, 0.95-3.64). Genetic variants associated with essential hypertension, mainly SBP, increase the risk of severe bevacizumab-induced hypertension., (© 2022 The Authors. Clinical Pharmacology & Therapeutics © 2022 American Society for Clinical Pharmacology and Therapeutics.)

Increasing prevalence of infections caused by antimicrobial-resistant gram-negative bacteria represents a global health crisis, and while several novel therapies that target various aspects of antimicrobial resistance have been introduced in recent years, few are currently approved for children. Ceftazidime-avibactam is a novel β-lactam β-lactamase inhibitor combination approved for adults and children 3 months and older with complicated intra-abdominal infection, and complicated urinary tract infection or hospital-acquired ventilator-associated pneumonia (adults only in the United States) caused by susceptible gram-negative bacteria. Extensive population pharmacokinetic (PK) data sets for ceftazidime and avibactam obtained during the adult clinical development program were used to iteratively select, modify, and validate the approved adult dosage regimen (2,000-500 mg by 2-hour intravenous (IV) infusion every 8 hours (q8h), with adjustments for renal function). Following the completion of one phase I (NCT01893346) and two phase II ceftazidime-avibactam studies (NCT02475733 and NCT02497781) in children, adult PK data sets were updated with pediatric PK data. This paper describes the development of updated combined adult and pediatric population PK models and their application in characterizing the population PK of ceftazidime and avibactam in children, and in dose selection for further pediatric evaluation. The updated models supported the approval of ceftazidime-avibactam pediatric dosage regimens (all by 2-hour IV infusion) of 50-12.5 mg/kg (maximum 2,000-500 mg) q8h for those ≥6 months to 18 years old, and 40-10 mg/kg q8h for those ≥3 to 6 months old with creatinine clearance > 50 mL/min/1.73 m 2 ., (© 2021 Pfizer Inc. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The European Union's Pediatric Regulation has strengthened the development of medicines for children in Europe through its system of obligations and rewards. However, opportunities remain to further optimize pediatric medicine developments, notably in relation to the implementation of the regulatory framework. This paper therefore describes bottlenecks identified by industry that occur during the medicinal development process, including those relating to the scientific advice process, pediatric investigation plan (PIP) development, compliance checks, and study submissions, and offers some considerations and insights to address these. Considerations, which are workable within the current legislative framework, focus on an integrated scientific discussion, optimization of PIP procedures and compliance checks, and an alignment of study-reporting requirements., (© 2021 Sanofi. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The predictive performance of physiologically-based pharmacokinetics (PBPK) models for pharmacokinetics (PK) in renal impairment (RI) and hepatic impairment (HI) populations was evaluated using clinical data from 29 compounds with 106 organ impairment study arms were collected from 19 member companies of the International Consortium for Innovation and Quality in Pharmaceutical Development. Fifty RI and 56 HI study arms with varying degrees of organ insufficiency along with control populations were evaluated. For RI, the area under the curve (AUC) ratios of RI to healthy control were predicted within twofold of the observed ratios for > 90% (N = 47/50 arms). For HI, > 70% (N = 43/56 arms) of the hepatically impaired to healthy control AUC ratios were predicted within twofold. Inaccuracies, typically overestimation of AUC ratios, occurred more in moderate and severe HI. PBPK predictions can help determine the need and timing of organ impairment study. It may be suitable for predicting the impact of RI on PK of drugs predominantly cleared by metabolism with varying contribution of renal clearance. PBPK modeling may be used to support mild impairment study waivers or clinical study design., (© 2020 Merck Sharp & Dohme Corp. Clinical Pharmacology & Therapeutics © 2020 American Society for Clinical Pharmacology and Therapeutics.)

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., (© 2020 The Authors Clinical Pharmacology & Therapeutics © 2020 American Society for Clinical Pharmacology and Therapeutics.)

Drug development in oncology commonly exploits the tools of molecular biology to gain therapeutic benefit through reprograming of cellular responses. In immuno-oncology (IO) the aim is to direct the patient's own immune system to fight cancer. After remarkable successes of antibodies targeting PD1/PD-L1 and CTLA4 receptors in targeted patient populations, the focus of further development has shifted toward combination therapies. However, the current drug-development approach of exploiting a vast number of possible combination targets and dosing regimens has proven to be challenging and is arguably inefficient. In particular, the unprecedented number of clinical trials testing different combinations may no longer be sustainable by the population of available patients. Further development in IO requires a step change in selection and validation of candidate therapies to decrease development attrition rate and limit the number of clinical trials. Quantitative systems pharmacology (QSP) proposes to tackle this challenge through mechanistic modeling and simulation. Compounds' pharmacokinetics, target binding, and mechanisms of action as well as existing knowledge on the underlying tumor and immune system biology are described by quantitative, dynamic models aiming to predict clinical results for novel combinations. Here, we review the current QSP approaches, the legacy of mathematical models available to quantitative clinical pharmacologists describing interaction between tumor and immune system, and the recent development of IO QSP platform models. We argue that QSP and virtual patients can be integrated as a new tool in existing IO drug development approaches to increase the efficiency and effectiveness of the search for novel combination therapies., (© 2020 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Defining an appropriate and efficient assessment of drug-induced corrected QT interval (QTc) prolongation (a surrogate marker of torsades de pointes arrhythmia) remains a concern of drug developers and regulators worldwide. In use for over 15 years, the nonclinical International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) S7B and clinical ICH E14 guidances describe three core assays (S7B: in vitro hERG current & in vivo QTc studies; E14: thorough QT study) that are used to assess the potential of drugs to cause delayed ventricular repolarization. Incorporating these assays during nonclinical or human testing of novel compounds has led to a low prevalence of QTc-prolonging drugs in clinical trials and no new drugs having been removed from the marketplace due to unexpected QTc prolongation. Despite this success, nonclinical evaluations of delayed repolarization still minimally influence ICH E14-based strategies for assessing clinical QTc prolongation and defining proarrhythmic risk. In particular, the value of ICH S7B-based "double-negative" nonclinical findings (low risk for hERG block and in vivo QTc prolongation at relevant clinical exposures) is underappreciated. These nonclinical data have additional value in assessing the risk of clinical QTc prolongation when clinical evaluations are limited by heart rate changes, low drug exposures, or high-dose safety considerations. The time has come to meaningfully merge nonclinical and clinical data to enable a more comprehensive, but flexible, clinical risk assessment strategy for QTc monitoring discussed in updated ICH E14 Questions and Answers. Implementing a fully integrated nonclinical/clinical risk assessment for compounds with double-negative nonclinical findings in the context of a low prevalence of clinical QTc prolongation would relieve the burden of unnecessary clinical QTc studies and streamline drug development., (© 2020 Amgen, Inc.; Pfizer, Inc.; Takeda Inc.; Bayer; Novartis; Merck; Bristol-Myers Squibb; and Janssen. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Minimal residual disease (MRD) is an important emerging clinical end point in chronic lymphocytic leukemia (CLL). The objective of this research was to develop an integrated mechanistic model to evaluate the impact of venetoclax-rituximab combination therapy on MRD kinetics. Using data from 435 patients with relapsed or refractory CLL, an integrated model was developed and validated that accounted for venetoclax dosing and pharmacokinetics, rituximab treatment, absolute lymphocyte count, and blood and bone marrow (BM) MRD data. Simulations of venetoclax-rituximab (six cycles) combination predicted the proportion (90% confidence interval) of patients with BM MRD below 10 -4 to be 57% (54-61%) and 63% (59-67%) at 12 and 24 months of treatment, respectively. Continued venetoclax treatment to 48 months only increased the predicted rate of negative BM MRD to 66% (63-70%). These results indicate that treatment with venetoclax-rituximab combination for a finite 2-year period would nearly maximize the rate of negative BM MRD (< 10 -4 ). Preliminary clinical data agree with these predictions and more long-term follow-up data are awaited to confirm the same., (© 2020 AbbVie Inc. Clinical Pharmacology & Therapeutics © 2020 American Society for Clinical Pharmacology and Therapeutics.)

Physiologically-based pharmacokinetic (PBPK) modeling has been extensively used to quantitatively translate in vitro data and evaluate temporal effects from drug-drug interactions (DDIs), arising due to reversible enzyme and transporter inhibition, irreversible time-dependent inhibition, enzyme induction, and/or suppression. PBPK modeling has now gained reasonable acceptance with the regulatory authorities for the cytochrome-P450-mediated DDIs and is routinely used. However, the application of PBPK for transporter-mediated DDIs (tDDI) in drug development is relatively uncommon. Because the predictive performance of PBPK models for tDDI is not well established, here, we represent and discuss examples of PBPK analyses included in regulatory submission (the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the Pharmaceuticals and Medical Devices Agency (PMDA)) across various tDDIs. The goal of this collaborative effort (involving scientists representing 17 pharmaceutical companies in the Consortium and from academia) is to reflect on the use of current databases and models to address tDDIs. This challenges the common perceptions on applications of PBPK for tDDIs and further delves into the requirements to improve such PBPK predictions. This review provides a reflection on the current trends in PBPK modeling for tDDIs and provides a framework to promote continuous use, verification, and improvement in industrialization of the transporter PBPK modeling., (© 2019 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Exposure-response analyses of upadacitinib (UPA) key efficacy and safety end points (3,685 and 4,577 subjects for efficacy and safety, respectively) using data from phase II and phase III rheumatoid arthritis (RA) studies were conducted to support benefit-risk assessment. Percentage of subjects achieving American College of Rheumatology (ACR)20/50/70, disease activity score 28 (C-reactive protein) (DAS28-CRP) ≤ 3.2, and DAS28-CRP < 2.6 increased with increasing UPA plasma exposures. With the small number of observed safety events, no clear trends for exposure-response relationships were identified for pneumonia, herpes zoster infection, changes in platelet count, lymphopenia (Grade ≥ 4), or neutropenia (Grade ≥ 3) up to Week 26. Shallow exposure-response relationships were observed for > 2 g/dL decrease in hemoglobin, lymphopenia Grade ≥ 3 at Week 12/14, and serious infections at Week 24/26. Exposure-efficacy analyses demonstrate that UPA 15 mg q.d. (once daily) dose provided the optimal benefit-risk in RA through maximizing efficacy with only small incremental benefit with 30 mg q.d.; and with consistency across RA subpopulations and with UPA monotherapy or combination with conventional synthetic disease-modifying antirheumatic drugs., (© 2019 AbbVie. Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Our goal was to assess the enrichment utility of hippocampal volume (HV) as an enrichment biomarker in amnestic mild cognitive impairment (aMCI) clinical trials, and, hence, develop an HV neuroimaging-informed clinical trial enrichment tool. Modeling of integrated longitudinal patient-level data came from open-access natural history studies in patients diagnosed with aMCI-the Alzheimer's Disease Neuroimaging Initiative (ADNI)-1 and ADNI-2-and indicated that a decrease of 1 cm 3 with respect to the analysis dataset median baseline intracranial volume-adjusted HV (ICV-HV; ~ 5 cm 3 ) is associated with > 50% increase in disease progression rate as measured by the Clinical Dementia Rating Scale-Sum of Boxes. Clinical trial simulations showed that the inclusion of aMCI subjects with baseline ICV-HV below the 84th or 50th percentile allowed an approximate reduction in trial size of at least 26% and 55%, respectively. This clinical trial enrichment tool can help design more efficient and informative clinical trials., (© 2020 The Authors Clinical Pharmacology & Therapeutics © 2020 American Society for Clinical Pharmacology and Therapeutics.)

Upadacitinib plasma concentrations, efficacy, and safety data from 216 subjects with moderate-to-severe active Crohn's disease (CD) from the 16-week induction period of the CELEST study were analyzed to characterize upadacitinib exposure-response relationships in CD. Subjects in CELEST received either placebo or upadacitinib (3, 6, 12, 24 mg b.i.d. or 24 mg q.d.). Exposure-response models were developed and utilized to simulate efficacy of induction doses of the immediate-release (IR) and extended-release (ER) formulations. Upadacitinib exposures associated with 18-24 mg b.i.d. (IR formulation) or 45-60 mg q.d. (ER formulation) are estimated to have greater efficacy during 12-week induction in patients with CD compared with lower doses. No exposure-response relations were observed with decreases in hemoglobin or lymphocytes at week 16 or with herpes zoster infections, pneumonia, or serious infections during 16 weeks of treatment in this study. These analyses informed the selection of upadacitinib induction dose for phase III studies in CD., (© 2019 AbbVie Inc. Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Risankizumab has demonstrated efficacy in phase III trials in patients with moderate-to-severe plaque psoriasis. The exposure-response relationships for risankizumab efficacy (Psoriasis Area and Severity Index (PASI)75, PASI90, PASI100, and static Physician's Global Assessment (sPGA)0/1) at week 16 (N = 1,732) and week 52 (N = 598) as well as safety (incidence of any adverse event, serious adverse event, infection and infestation, or serious infection) over up to 52 weeks were characterized using the data from risankizumab phase II and III clinical trials in patients with moderate-to-severe plaque psoriasis. Impact of clinically relevant covariates was evaluated. Risankizumab phase III regimen (150 mg subcutaneously at weeks 0, 4, and every 12 weeks thereafter) achieved the plateau of the exposure-efficacy relationships with model-estimated PASI90 and sPGA0/1 response probabilities of 77%, and 87%, respectively, at week 16 and 85%, and 88%, respectively, at week 52. There was no apparent relationship between risankizumab plasma exposure and the evaluated safety variables., (© 2019 AbbVie Inc. Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Risankizumab, an anti-interleukin-23 monoclonal antibody, achieved significantly (P < 0.001) greater Psoriasis Area and Severity Index (PASI) and static Physician Global Assessment (sPGA) clear or almost clear (0/1) responses than adalimumab in a phase III trial in patients with moderate-to-severe psoriasis. Meta-analyses of the PASI 50, PASI 75, PASI 90, PASI 100, and sPGA0/1 responses after 16 weeks of treatment from eight (three for risankizumab and five for adalimumab) randomized, placebo-controlled trials were conducted to estimate the efficacy difference between risankizumab and adalimumab. For PASI 75, PASI 90, PASI 100, and sPGA0/1 responses, the estimated effect differences (95% confidence interval) between risankizumab and adalimumab were 15.2% (10.1%, 20.4%), 23.7% (15.7%, 31.2%), 20.8% (13.0%, 28.7%), and 20.1% (13.7%, 26.1%), respectively. These results were consistent with the observed efficacy difference from the head-to-head phase III trial, which was not included in the meta-analyses, providing independent, confirmatory evidence of the superior efficacy of risankizumab compared with adalimumab for treatment of moderate-to-severe psoriasis., (© 2019 AbbVie Inc. Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The relationships between upadacitinib, an oral selective Janus kinase 1 inhibitor, plasma exposures, and its efficacy (assessed by the American College of Rheumatology 20%/50%/70% responses over time) in moderate-to-severe active rheumatoid arthritis (RA) were characterized using data from 574 patients, on background methotrexate and inadequate response to methotrexate or anti-TNF therapy, from two phase II trials conducted with twice-daily dosing of an immediate-release formulation. The developed time-continuous Markov models were used to simulate efficacy of once-daily (q.d.). regimens of upadacitinib extended-release incorporating sources of uncertainty. Upadacitinib plasma concentrations associated with 15 and 30 mg extended-release q.d. doses were predicted to achieve that plateau of response across RA subpopulations. Results from these analyses provided the rationale that supported selection and de-risked evaluation of upadacitinib extended-release doses for the first time in >4,000 patients in five large phase III trials., (© 2019 AbbVie Inc. Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.)