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Pneumonitis is a potentially life-threatening complication of anticancer therapy, and future treatment decisions may be informed by characterizing patients receiving therapies in the real-world setting. In this study, the incidence of treatment-associated pneumonitis (TAP) was compared among patients with advanced non–small cell lung cancer receiving immune checkpoint inhibitors (ICI) or chemotherapies in either of two settings: randomized clinical trials (RCT) or real world data (RWD)-based clinical practice. Pneumonitis cases were identified using International Classification of Diseases codes (for RWD), or the Medical Dictionary for Regulatory Activities preferred terms (for RCTs). TAP was defined as pneumonitis diagnosed during treatment or within 30 days of the last treatment administration. Overall TAP rates in the RWD cohort were lower [ICI: 1.9%; 95% confidence interval (CI), 1.2–3.2; chemotherapy: 0.8%; 95% CI, 0.4–1.6] than overall rates in the RCT cohort (ICI: 5.6%; 95% CI, 5.0–6.2; chemotherapy: 1.2%; 95% CI, 0.9–1.5). Overall RWD TAP rates were similar to grade 3+ RCT TAP rates (ICI: 2.0%; 95% CI, 1.6–2.3; chemotherapy: 0.6%; 95% CI, 0.4–0.9). In both cohorts, higher TAP incidence was observed among patients with a past medical history of pneumonitis than those without, regardless of treatment group. On the basis of this sizable study leveraging RWD, TAP incidence was low in the RWD cohort, likely in part due to methodology used for RWD focusing on clinically significant cases. Past medical history of pneumonitis was associated with TAP in both cohorts.Significance:Pneumonitis is a potentially life-threatening complication of anticancer treatment. As treatment options expand, management decisions become increasingly complex, and there is a greater need to understand the safety profiles of the treatment options in the real-world setting. Real-world data serve as an additional source of valuable information to complement clinical trial data and inform understanding of toxicity in patients with non–small cell lung cancer receiving ICIs or chemotherapies.

Pneumonitis is a potentially life-threatening complication of anticancer therapy, and future treatment decisions may be informed by characterizing patients receiving therapies in the real-world setting. In this study, the incidence of treatment-associated pneumonitis (TAP) was compared among patients with advanced non–small cell lung cancer receiving immune checkpoint inhibitors (ICI) or chemotherapies in either of two settings: randomized clinical trials (RCT) or real world data (RWD)-based clinical practice. Pneumonitis cases were identified using International Classification of Diseases codes (for RWD), or the Medical Dictionary for Regulatory Activities preferred terms (for RCTs). TAP was defined as pneumonitis diagnosed during treatment or within 30 days of the last treatment administration. Overall TAP rates in the RWD cohort were lower [ICI: 1.9%; 95% confidence interval (CI), 1.2–3.2; chemotherapy: 0.8%; 95% CI, 0.4–1.6] than overall rates in the RCT cohort (ICI: 5.6%; 95% CI, 5.0–6.2; chemotherapy: 1.2%; 95% CI, 0.9–1.5). Overall RWD TAP rates were similar to grade 3+ RCT TAP rates (ICI: 2.0%; 95% CI, 1.6–2.3; chemotherapy: 0.6%; 95% CI, 0.4–0.9). In both cohorts, higher TAP incidence was observed among patients with a past medical history of pneumonitis than those without, regardless of treatment group. On the basis of this sizable study leveraging RWD, TAP incidence was low in the RWD cohort, likely in part due to methodology used for RWD focusing on clinically significant cases. Past medical history of pneumonitis was associated with TAP in both cohorts.Significance:Pneumonitis is a potentially life-threatening complication of anticancer treatment. As treatment options expand, management decisions become increasingly complex, and there is a greater need to understand the safety profiles of the treatment options in the real-world setting. Real-world data serve as an additional source of valuable information to complement clinical trial data and inform understanding of toxicity in patients with non–small cell lung cancer receiving ICIs or chemotherapies.

Supplementary Table 1. Pneumonitis defined using A) ICD-9 and B) ICD-10 codes that included ‘pneumonitis’ or associated concepts in the Unified Medical Language System, with Bidirectional General Equivalence Mappings used to identify equivalent terms between ICD-9 and ICD-10 in the Real World Data (RWD) cohortSupplementary Table 2: ICD codes used to identify history of chronic lung condition in the Real World Data (RWD) cohortSupplementary Table 3. Selection of clinical trial (RCT) populationSupplementary Table 4. Incidence of Treatment-Associated Pneumonitis in the Randomized Clinical Trial (RCT) Cohort and the Real World Data (RWD) Cohort based on sensitivity analysesSupplementary Table 5. Treatment-associated pneumonitis counts by grade in the Randomized Clinical Trial (RCT) cohortSupplementary Table 6. Demographic and Clinical Characteristics of Patients With and Without Radiation Therapy (RT) status available in the Real World Data (RWD) Cohort

Transporters govern the access of molecules to cells or their exit from cells, thereby controlling the overall distribution of drugs to their intracellular site of action. Clinically relevant drug-drug interactions mediated by transporters are of increasing interest in drug development. Drug transporters, acting alone or in concert with drug metabolizing enzymes, can play an important role in modulating drug absorption, distribution, metabolism, and excretion, thus affecting the pharmacokinetics and/or pharmacodynamics of a drug. Dr. Kathy Giacomini from the University of California, San Francisco is one of the world leaders in transporters and pharmacogenetics with key contributions to transporter science. Her contributions to transporter science are noteworthy. This review paper will summarize Dr. Giacomini’s key contributions and influence on transporters in regulatory science in the past two decades. Regulatory science research highlighted in this review covers various aspects of transporter science, including understanding the effect of renal impairment on transporters, transporter ontogeny, biomarkers for transporters, and interactions of excipients with transporters affecting drug absorption. SIGNIFICANCE STATEMENT: This review paper highlights Dr. Giacomini’s key contributions and influence on transporters in regulatory science in the past two decades. She has been at the cutting edge of science pertaining to drug transport, drug disposition, and regulatory science, leading to a new era of translational sciences pertaining to drug disposition and transporter biology. Her research has and will continue to bring enormous impact on gaining new knowledge in guiding drug development and inspire scientists from all sectors in the field.

Changes that accompany older age can alter the pharmacokinetics (PK), pharmacodynamics (PD), and likelihood of adverse effects (AEs) of a drug. However, older adults, especially the oldest or those with multiple chronic health conditions, polypharmacy, or frailty, are often under-represented in clinical trials of new drugs. Deficits in the current conduct of clinical evaluation of drugs for older adults and potential steps to fill those knowledge gaps are presented in this communication. The most important step is to increase clinical trial enrollment of older adults who are representative of the target treatment population. Unnecessary eligibility criteria should be eliminated. Physical and financial barriers to participation should be removed. Incentives could be created for inclusion of older adults. Enrollment goals should be established based on intended treatment indications, prevalence of the condition, and feasibility. Relevant clinical pharmacology data need to be obtained early enough to guide dosing and reduce risk for participation of older adults. Relevant PK and PD data as well as patient-centered outcomes should be measured during trials. Trial data should be analyzed for differences in PK, PD, effectiveness, and safety arising from differences in age or from the presence of conditions common in older adults. Postmarket evaluations with real-world evidence and drug labeling updates throughout the product lifecycle reflecting new knowledge are also needed. A comprehensive plan is needed to ensure adequate evaluation of the safety and effectiveness of drugs in older adults.

Assessment of transporter-mediated drug-drug interaction (DDI) is integral to drug development. A risk-based approach leveraging in vitro, in vivo, and in silico information is used to evaluate the DDI liability of drugs and inform the instructions of use. While tremendous advances have been made in recent decades, there are knowledge gaps warranting further research. Herein, we focus on select areas to advance assessment of DDI potential for drugs as substrates, inhibitors, or inducers of certain transporters.

Nonclinical testing has served as a foundation for evaluating potential risks and effectiveness of investigational new drugs in humans. However, the current two‐dimensional (2D) in vitro cell culture systems cannot accurately depict and simulate the rich environment and complex processes observed in vivo, whereas animal studies present significant drawbacks with inherited species‐specific differences and low throughput for increased demands. To improve the nonclinical prediction of drug safety and efficacy, researchers continue to develop novel models to evaluate and promote the use of improved cell‐ and organ‐based assays for more accurate representation of human susceptibility to drug response. Among others, the three‐dimensional (3D) cell culture models present physiologically relevant cellular microenvironment and offer great promise for assessing drug disposition and pharmacokinetics (PKs) that influence drug safety and efficacy from an early stage of drug development. Currently, there are numerous different types of 3D culture systems, from simple spheroids to more complicated organoids and organs‐on‐chips, and from single‐cell type static 3D models to cell co‐culture 3D models equipped with microfluidic flow control as well as hybrid 3D systems that combine 2D culture with biomedical microelectromechanical systems. This article reviews the current application and challenges of 3D culture systems in drug PKs, safety, and efficacy assessment, and provides a focused discussion and regulatory perspectives on the liver‐, intestine‐, kidney‐, and neuron‐based 3D cellular models.

Evaluating the potential of new drugs and their metabolites to cause drug-drug interactions (DDIs) is critical for understanding drug safety and efficacy. Although multiple analyses of proprietary metabolite testing data have been published, no systematic analyses of metabolite data collected according to current testing criteria have been conducted. To address this knowledge gap, 120 new molecular entities approved between 2013 and 2018 were reviewed. Comprehensive data on metabolite-to-parent area under the curve ratios (AUCM /AUCP ), inhibitory potency of parent and metabolites, and clinical DDIs were collected. Sixty-four percent of the metabolites quantified in vivo had AUCM /AUCP ≥ 0.25 and 75% of these metabolites were tested for cytochrome P450 (CYP) inhibition in vitro, resulting in 15 metabolites with potential DDI risk identification. Although 50% of the metabolites with AUCM /AUCP

This study applied modeling and simulation (MS) approaches to evaluate the sensitivity of pegfilgrastim pharmacokinetics (PKs) and pharmacodynamics (PDs) to changes in dose amount, and linear or nonlinear clearance (CL) over pegfilgrastim subcutaneous dose of 2-6 mg. A previously published model was adapted to better describe pegfilgrastim PK and PD data in healthy subjects and used in simulation. Nonlinear CL accounts for 98% and 77%, respectively, of the total CL of pegfilgrastim at 2 and 6 mg. The sensitivity analyses showed: (i) PK of 2 and 6 mg doses are similarly sensitive to detect differences for a 5% change in dose; (ii) PK of 2 mg dose is more sensitive to changes in receptor binding affinity, a model parameter for nonlinear CL, and a product quality attribute characterized with orthogonal methods as part of demonstrating analytical similarity between products; (iii) PK of approved 6 mg dose is more sensitive to changes in linear CL, which has not been associated with any specific product quality attributes, and (iv) the PDs are not sensitive to changes in linear or nonlinear CL. Taken together, our analyses support that the approved pegfilgrastim dose of 6 mg is appropriate for detecting differences between a biosimilar and the reference products in pegfilgrastim PK and PD similarity studies. The described MS approaches can be adopted to support dose selection for biosimilars with nonlinear PK and complex PK-PD interplay.

Science is constantly evolving. As a result, novel tools as well as new issues are arising for clinical pharmacologists. In this chapter, we will discuss some emerging topics in clinical pharmacology, including model-informed drug development, real-world data and real-world evidence, and digital health technologies, as well as the microbiome and its impact on drug effect and treatment outcome.

A treatment gap exists for pediatric patients with renal impairment. Alterations in renal clearance and metabolism of drugs render standard dosage regimens inappropriate and may lead to drug toxicity, but these studies are not routinely conducted during drug development. The objective of this study was to examine the clinical evidence behind current renal impairment dosage recommendations for pediatric patients in a standard pediatric dosing handbook. The sources of recommendations and comparisons included the pediatric dosing handbook (Lexicomp), the U.S. Food and Drug Administration-approved manufacturer’s labels, and published studies in the literature. One hundred twenty-six drugs in Lexicomp had pediatric renal dosing recommendations. Only 14% (18 of 126) of Lexicomp pediatric renal dosing recommendations referenced a pediatric clinical study, and 15% of manufacturer’s labels (19 of 126) described specific dosing regimens for renally impaired pediatric patients. Forty-two products had published information on pediatric renal dosing, but 19 (45%) were case studies. When pediatric clinical studies were not referenced in Lexicomp, the renal dosing recommendations followed the adult and pediatric dosing recommendations on the manufacturer’s label. Clinical evidence in pediatric patients does not exist for most renal dosing recommendations in a widely used pediatric dosing handbook, and the adult renal dosing recommendations from the manufacturer’s label are currently the primary source of pediatric renal dosing information.

There has been growing interest in developing therapeutic agents and other consumer products derived from cannabis and its components. To date, the US Food and Drug Administration (FDA) has not approved cannabis as a safe and effective drug for any indication. With the progressive state legalization of cannabis for medical use, healthcare providers and consumers must understand what is known about the safety and efficacy linked to cannabis.

ImportanceOlder age may be accompanied by changes in the pharmacokinetics or pharmacodynamics or both of medications that can result in altered safety and efficacy profiles.ObjectiveTo assess representation of older adults in clinical trials of new drug applications (NDAs) and biologics license applications (BLAs).Design, Setting, and ParticipantsThis cross-sectional study analyzed US Food and Drug Administration (FDA) data for NDAs and BLAs approved from 2010 through 2019. Age distribution of clinical trial participants was compared with age distribution of the US population with the disease or disorder (prevalent population). Data were from adults enrolled in registration trials for depression, heart failure, insomnia, non–small cell lung cancer (NSCLC), nonvalvular atrial fibrillation (NVAF) stroke prevention, osteoporosis, and type 2 diabetes or adults sampled from US prevalent population in community-dwelling health data. Data were analyzed from November 2020 to February 2021.ExposuresTrial enrollment.Main Outcomes and MeasuresRepresentativeness of trial populations was assessed by the participation to prevalence ratio (PPR) defined as the percentage of patients by age group among clinical trial participants to the percentage of patients by age group among US prevalent population.ResultsData from 166 clinical trials (229 558 participants) for 44 NDAs and BLAs were analyzed. The most consistent finding was the limited enrollment of the oldest age groups, namely those 75 years and above for type 2 diabetes and NSCLC, and 80 years and above for NVAF stroke prevention, insomnia, heart failure, and osteoporosis. Adults aged 60 to 74 years were enrolled in equal or greater proportion than the US prevalent population.Conclusions and RelevanceIn this cross-sectional study, underrepresentation of the oldest adults existed during evaluation of new drugs and biologics, yet the older adults may represent significant proportions of the treatment population. Closing the representation gap between clinical trial enrollment and potential treatment populations is essential for safe and effective use of new drugs and biologics.

The presence of circulating targets and antidrug antibodies can influence the ability of a bioanalytical method to measure therapeutic protein (TP) concentration relevant to exposure-response evaluations. This project surveyed biosimilar submissions for their bioanalytical methods. Survey results revealed that 97% of pharmacokinetic methods designed to measure theoretically free or partial-free TPs with respect to target indeed measured free or partial-free TPs when considering experimental testing results for target effects. Antidrug antibody effect is less often evaluated. The observed trend of measuring biologically active forms of TP is consistent with the scientific understanding that pharmacokinetics of biologically active forms is more likely to be relevant to the clinical responses and evaluation of clinically meaningful differences to contribute to biosimilarity assessments.

Background:Drug-induced Liver Injury (DILI) has received increasing attention over the past decades, as it represents the leading cause of drug failure and attrition. One of the most prevalent and severe forms of DILI involves the toxic accumulation of bile acids in the liver, known as Drug-induced Cholestasis (DIC). Traditionally, DIC is studied by exploring the inhibition of hepatic transporters such as Bile Salt Export Pump (BSEP) and multidrug resistance-associated proteins, predominantly through vesicular transport assays. Although this approach has identified numerous drugs that alter bile flow, many DIC drugs do not demonstrate prototypical transporter inhibition, but rather are associated with alternative mechanisms.Methods:We undertook a focused literature search on DIC and biliary transporters and analyzed peer-reviewed publications over the past two decades or so.Results:We have summarized the current perception regarding DIC, biliary transporters, and transcriptional regulation of bile acid homeostasis. A growing body of literature aimed to identify alternative mechanisms in the development of DIC has been evaluated. This review also highlights current in vitro approaches used for prediction of DIC.Conclusion:Efforts have continued to focus on BSEP, as it is the primary route for hepatic biliary clearance. In addition to inhibition, drug-induced BSEP repression or the combination of these two has emerged as important alternative mechanisms leading to DIC. Furthermore, there has been an evolution in the approaches to studying DIC including 3D cell cultures and computational modeling.

The recently enacted Prescription Drug User Fee Act (PDUFA) VI includes in its performance goals "enhancing regulatory science and expediting drug development." The key elements in "enhancing regulatory decision tools to support drug development and review" include "advancing model-informed drug development (MIDD)." This paper describes (i) the US Food and Drug Administration (FDA) Office of Clinical Pharmacology's continuing efforts in developing quantitative clinical pharmacology models (disease, drug, and clinical trial models) to advance MIDD, (ii) how emerging novel tools, such as organ-on-a-chip technologies or microphysiological systems, can provide new insights into physiology and disease mechanisms, biomarker identification and evaluation, and elucidation of mechanisms of adverse drug reactions, and (iii) how the single organ or linked organ microphysiological systems can provide critical system parameters for improved physiologically-based pharmacokinetic and pharmacodynamic evaluations. Continuous public-private partnerships are critical to advance this field and in the application of these new technologies in drug development and regulatory review.

Model-informed drug development (MIDD) refers to the application of a wide range of quantitative models in drug development to facilitate the decision-making process. MIDD was formally recognized in Prescription Drug User Fee Act (PDUFA) VI. There have been many regulatory applications of MIDD to address a variety of drug development and regulatory questions. These applications can be broadly classified into four categories: dose optimization, supportive evidence for efficacy, clinical trial design, and informing policy. Case studies, literature papers, and published regulatory documents are reviewed in this article to highlight some common features of these applications in each category. In addition to the further development and investment in these established domains of application, new technology, and areas, such as more mechanistic models, neural network models, and real-world data/evidence, are gaining attention, and more submissions and experiences are being accumulated to expand the application of model-based analysis to a wider scope.

With this issue of the Journal of Pharmaceutical Sciences, we celebrate the nearly 6 decades of contributions to mechanistic-based modeling and computational pharmaceutical sciences. Along with its predecessor, The Journal of the American Pharmaceutical Association: Scientific Edition first published in 1911, JPharmSci has been a leader in the advancement of pharmaceutical sciences beginning with its inaugural edition in 1961. As one of the first scientific journals focusing on pharmaceutical sciences, JPharmSci has established a reputation for publishing high-quality research articles using computational methods and mechanism-based modeling. The journal's publication record is remarkable. With over 15,000 articles, 3000 notes, and more than 650 reviews from industry, academia, and regulatory agencies around the world, JPharmSci has truly been the leader in advancing pharmaceutical sciences.

In the regulatory setting, clinical pharmacology focuses on the impact of intrinsic and extrinsic factors on inter-patient and intra-subject variability in drug exposure and response. This translational science contributes to the understanding of the benefit-risk profile in individual patients and the development of relevant therapeutic monitoring and management strategies. Clinical pharmacology also plays a major role in the development and qualification of drug development tools. This article presented some recent examples to illustrate the important roles of clinical pharmacology in drug development and evaluation. In addition, emerging trends in clinical pharmacology regulatory sciences were also discussed, including the Model-Informed Drug Development (MIDD) pilot program, the use of real-world data to generate real-world evidence, and leveraging advances in basic, biomedical, and clinical science into useful tools for drug development and evaluation. Continued advances in clinical pharmacology can be the basis of more rational and efficient drug development and improved access to new drug treatments that are tailored to the patient to achieve better efficacy and safety.

Patients with multiple chronic conditions, including more advanced chronic kidney disease (CKD), are often excluded from clinical trials, creating challenges in deriving appropriate dosing information and labeling. This article summarizes the May 7th , 2019 U.S. Food and Drug Administration Pharmaceutical Science and Clinical Pharmacology Advisory Committee Meeting, which solicited expert opinions on how to enroll patients with more advanced CKD into clinical trials as well as the assumptions behind and different approaches of exposure-matching.

Since 2016, results from physiologically based pharmacokinetic (PBPK) analyses have been routinely found in the clinical pharmacology section of regulatory applications submitted to the US Food and Drug Administration (FDA). In 2018, the Food and Drug Administration's Office of Clinical Pharmacology published a commentary summarizing the application of PBPK modeling in the submissions it received between 2008 and 2017 and its impact on prescribing information. In this commentary, we provide an update on the application of PBPK modeling in submissions received between 2018 and 2019 and highlight a few notable examples.

Creatinine is widely used as a biomarker of glomerular filtration, and, hence, renal function. However, transporter-mediated secretion also contributes to its renal clearance, albeit to a lesser degree. Inhibition of these transporters causes transient serum creatinine elevation, which can be mistaken as impaired renal function. The current study developed mechanistic models of creatinine kinetics within physiologically based framework accounting for multiple transporters involved in creatinine renal elimination, assuming either unidirectional or bidirectional-OCT2 transport (driven by electrochemical gradient). Robustness of creatinine models was assessed by predicting creatinine-drug interactions with 10 perpetrators; performance evaluation accounted for 5% intra-individual variability in serum creatinine. Models showed comparable predictive performances of the maximum steady-state effect regardless of OCT2 directionality assumptions. However, only the bidirectional- OCT2 model successfully predicted the minimal effect of ranitidine. The dynamic nature of models provides clear advantage to static approaches and most advanced framework for evaluating interplay between multiple processes in creatinine renal disposition.

Translation of in vitro antiviral activity to the in vivo setting is crucial to identify potentially effective dosing regimens of hydroxychloroquine. In vitro 50%/90% maximal effective concentration values for hydroxychloroquine should be compared to the in vivo free extracellular tissue concentration, which is similar to the free plasma hydroxychloroquine concentration.

Biologic-device combination products using prefilled syringes (PFSs) and autoinjectors (AIs) are popular for biological products administered subcutaneously. Pharmacokinetic (PK) comparability studies commonly provide the scientific data to support introduction of AI presentations via bridging with PFS. A survey of biological products approved by FDA's Center for Drug Evaluation and Research identified 17 biologics license applications (BLAs) with both PFS and AI presentations for subcutaneous (SC) administration, including 16 approved on February 1, 2018, and one with AI presentation under review. A systematic review on the device parameters and the PK comparability studies bridging the two presentations was conducted. Subsequently, whether device parameters or the PK study design may have influenced the PK comparability study results was evaluated. The reported device parameters for AI and PFS are generally consistent across BLAs, whereas the approach to assess PK comparability varied, including the study design. Most PK comparability studies met bioequivalence (BE) criteria. Upon inspection of the studies that did not meet BE criteria, injection depth of AI and the injection site for either AI or PFS were identified as potential influencing factors to the outcome of PK comparability study. This study represents an initial attempt to identify the potential influencing factors on device bridging, including the characteristics of the device and the clinical pharmacology study. These findings may inform the combination product development strategy, specifically design considerations for device and PK comparability studies.

PURPOSE: The bile salt export pump (BSEP), a key player in hepatic bile acid clearance, has been the center of research on drug-induced cholestasis. However, such studies focus primarily on the direct inhibition of BSEP, often overlooking the potential impact of transcriptional repression. This work aims to explore the disruption of bile acid efflux caused by drug-induced BSEP repression. METHODS: BSEP activity was analyzed in human primary hepatocytes (HPH) using a traditional biliary-clearance experiment and a modified efflux assay, which includes a 72-h pretreatment prior to efflux measurement. Relative mRNA and protein expressions were examined by RT-PCR and Western blotting, respectively. RESULTS: Metformin concentration-dependently repressed BSEP expression in HPH. Although metformin did not directly inhibit BSEP activity, longer metformin exposure reduced BSEP transport function in HPH by down-regulating BSEP expression. BSEP repression by metformin was found to be AMP-activated protein kinase-independent. Additional screening of 10 reported cholestatic non-BSEP inhibitors revealed that the anti-cancer drug tamoxifen also markedly repressed BSEP expression and reduced BSEP activity in HPH. CONCLUSIONS: Repression of BSEP alone is sufficient to disrupt hepatic bile acid efflux. Metformin and tamoxifen appear to be prototypes of a class of BSEP repressors that may cause drug-induced cholestasis through gene repression instead of direct BSEP inhibition.

Author(s): Yee, Sook Wah; Do, Thao P; Huang, Shiew-Mei; Krauss, Ronald M; Kusuhara, Hiroyuki; Sugiyama, Yuichi; Unadkat, Jashvant D; Giacomini, Kathleen M

Creatinine is the most common clinical biomarker of renal function. As a substrate for renal transporters, its secretion is susceptible to inhibition by drugs, resulting in transient increase in serum creatinine and false impression of damage to kidney. Novel physiologically based models for creatinine were developed here and (dis)qualified in a stepwise manner until consistency with clinical data. Data from a matrix of studies were integrated, including systems data (common to all models), proteomics-informed in vitro-in vivo extrapolation of all relevant transporter clearances, exogenous administration of creatinine (to estimate endogenous synthesis rate), and inhibition of different renal transporters (11 perpetrator drugs considered for qualification during creatinine model development and verification on independent data sets). The proteomics-informed bottom-up approach resulted in the underprediction of creatinine renal secretion. Subsequently, creatinine-trimethoprim clinical data were used to inform key model parameters in a reverse translation manner, highlighting best practices and challenges for middle-out optimization of mechanistic models.

There is a continued predisposition of concurrent use of drugs and botanical products. Consumers often self-administer botanical products without informing their health care providers. The perceived safety of botanical products with lack of knowledge of the interaction potential poses a challenge for providers and both efficacy and safety concerns for patients. Botanical–drug combinations can produce untoward effects when botanical constituents modulate drug metabolizing enzymes and/or transporters impacting the systemic or tissue exposure of concomitant drugs. Examples of pertinent scientific literature evaluating the interaction potential of commonly used botanicals in the US are discussed. Current methodologies that can be applied to advance our efforts in predicting drug interaction liability is presented. This review also highlights the regulatory science viewpoint on botanical–drug interactions and labeling implications. Keywords: Drug interaction, Botanical product, St. John's wort, Fruit juices, Regulatory science

Model-based analyses have been applied to influence various drug development and regulatory decisions in the last 2 decades. Applied models range from empirical models to highly complex mechanistic models. "Fit-for-purpose" has been the principle to determine the level of model complexity. While numerous case studies have been published to highlight the impact and value of model-based analyses, more experience and lessons are being accumulated to address new challenges and create more opportunities. The inclusion of Model-Informed Drug Development in the Prescription Drug User Fee Act (PDUFA) VI represents a new landmark for the field of quantitative clinical pharmacology.

Our recent studies have shown that chronic kidney disease (CKD) affects the pharmacokinetics (PKs) of cytochrome P450 (CYP)2D6-metabolized drugs, whereas effects were less evident on CYP3A4/5. Therefore, the effect of CKD on the disposition of CYP1A2-metabolized, CYP2C8-metabolized, CYP2C9-metabolized, CYP2C19-metabolized, and organic anion-transporting polypeptide (OATP)-transported drugs was investigated. We identified dedicated CKD studies with 6, 5, 6, 4, and 12 "model" substrates for CYP1A2, CYP2C8, CYP2C9, CYP2C19, and OATP, respectively. Our analyses suggest that clearance of OATP substrates decreases as kidney function declines. Similar trends were seen for CYP2C8; but overlap between some CYP2C8 and OATP substrates highlights that their interplay needs further investigation. In contrast, the effect of CKD on CYP1A2, CYP2C9, and CYP2C19 was variable and modest compared to CYP2C8 and OATP. This improved understanding of elimination-pathway-dependency in CKD is important to inform the need and conduct of PK studies in these patients for nonrenally eliminated drugs.