Leveraging in Vitro Models for Clinically Relevant Rare CYP2D6 Variants in Pharmacogenomics.

Cytochrome P450 2D6 (CYP2D6) is responsible for the metabolism of up to 20% of small-molecule drugs and therefore, may impact the safety and efficacy of medicines in broad therapeutic areas. CYP2D6 is highly polymorphic, and the frequency of variants can differ across racial and ethnic populations, significantly affecting enzymatic function and drug metabolism. However, rare variants of CYP2D6 present a unique challenge for academia, industry, and regulatory agencies alike due to the lack of feasibility of characterizing their clinical relevance in clinical trials, particularly in variants that exhibit population-specific frequencies in racial and ethnic groups that are poorly represented in clinical trials. Despite significant advancement in pharmacogenomics, the substrate specificity and related clinical relevance of these CYP2D6 rare variants remain largely unclear, and further efforts are warranted to characterize the burden of these variants on adverse drug reactions and drug efficacy. Thus, cell-based in vitro systems can be used to inform substrate-specific effects and the overall relevance of a rare variant. Liver microsomes, cell-based expression systems, ex vivo primary samples, and purified variant protein have all been used with various substrates to potentially predict the clinical impact of new substrates. In this review, we identify rare variants of CYP2D6 that demonstrate differences across races in prevalence and thus are often unassessed in clinical trials. Accordingly, we examine current pharmacogenomic in vitro models used to analyze the functional impact of these rare variants in a substrate-specific manner. SIGNIFICANCE STATEMENT: Variants of CYP2D6 play a clinically relevant role in drug metabolism, leading to potential safety and efficacy concerns. Although the influence of prevalent variants is often well characterized, rare variants are traditionally not included in clinical trials. This review captures the clinical relevance of rare variants in CYP2D6 by highlighting in vitro models that analyze their impact on the metabolism of CYP2D6 substrates.

Clinical pharmacology considerations for first-in-human clinical trials for enzyme replacement therapy.

Inborn errors of metabolism (IEM) such as lysosomal storage disorders (LSDs) are conditions caused by deficiency of one or more key enzymes, cofactors, or transporters involved in a specific metabolic pathway. Enzyme replacement therapy (ERT) provides an exogenous source of the affected enzyme and is one of the most effective treatment options for IEMs. In this paper, we review the first-in-human (FIH) protocols for ERT drug development programs supporting 20 Biologic License Applications (BLA) approved by the Center for Drug Evaluation and Research (CDER) at the US Food and Drug Administration (FDA) in the period of May 1994 to September 2023. We surveyed study design elements across these FIH protocols including study population, dosage form, dose selection, treatment duration, immunogenicity, biomarkers, and study follow-up. A total of 18 FIH trials from 20 BLAs were identified and of those, 72% (13/18) used single ascending dose (SAD) and/or multiple ascending dose (MAD) study design, 83% (15/18) had a primary objective of assessing the safety and tolerability, 72% (13/18) included clinical endpoint assessments, and 94% (17/18) included biomarker assessments as secondary or exploratory endpoints. Notably, the majority of ERT products tested the approved route of administration and the approved dose was tested in 83% (15/18) of FIH trials. At last, we offer considerations for the design of FIH studies.

FDA approval summary for lonafarnib (Zokinvy) for the treatment of Hutchinson-Gilford progeria syndrome and processing-deficient progeroid laminopathies.

The U.S. Food and Drug Administration recently approved lonafarnib as the first treatment for Hutchinson-Gilford progeria syndrome (HGPS) and processing-deficient progeroid laminopathies. This approval was primarily based on a comparison of patients with HGPS treated with lonafarnib in 2 open-label trials with an untreated patient cohort. With up to 11 years of follow-up, it was found that the lonafarnib treated patients with HGPS had a survival benefit of 2.5 years compared with the untreated patients with HGPS. This large treatment effect on the objective endpoint of mortality using a well-matched comparator group mitigated potential sources of bias and together with other evidence, established compelling evidence of a drug effect with benefits that outweighed the risks. This approval is an example of U.S. Food and Drug Administration's regulatory flexibility for a rare disease while ensuring that standards for drug approval are met.

PathFX provides mechanistic insights into drug efficacy and safety for regulatory review and therapeutic development.

Failure to demonstrate efficacy and safety issues are important reasons that drugs do not reach the market. An incomplete understanding of how drugs exert their effects hinders regulatory and pharmaceutical industry projections of a drug's benefits and risks. Signaling pathways mediate drug response and while many signaling molecules have been characterized for their contribution to disease or their role in drug side effects, our knowledge of these pathways is incomplete. To better understand all signaling molecules involved in drug response and the phenotype associations of these molecules, we created a novel method, PathFX, a non-commercial entity, to identify these pathways and drug-related phenotypes. We benchmarked PathFX by identifying drugs' marketed disease indications and reported a sensitivity of 41%, a 2.7-fold improvement over similar approaches. We then used PathFX to strengthen signals for drug-adverse event pairs occurring in the FDA Adverse Event Reporting System (FAERS) and also identified opportunities for drug repurposing for new diseases based on interaction paths that associated a marketed drug to that disease. By discovering molecular interaction pathways, PathFX improved our understanding of drug associations to safety and efficacy phenotypes. The algorithm may provide a new means to improve regulatory and therapeutic development decisions.

Personalized Cardiovascular Medicine Today: A Food and Drug Administration/Center for Drug Evaluation and Research Perspective.

Over the past decade, personalized medicine has received considerable attention from researchers, drug developers, and regulatory agencies. Personalized medicine includes identifying patients most likely to benefit and those most likely to experience adverse reactions in response to a drug, and tailoring therapy based on pharmacokinetics or pharmacodynamic response, as well. Perhaps most exciting is finding ways to identify likely responders through genetic, proteomic, or other tests, so that only likely responders will be treated. However, less precise methods such as identifying historical, demographic, or other indicators of increased or reduced responsiveness are also important aspects of personalized medicine. The cardiovascular field has not used many genetic or proteomic markers, but has regularly used prognostic variables to identify likely responders. The development of biomarker-based approaches to personalized medicine in cardiovascular disease has been challenging, in part, because most cardiovascular therapies treat acquired syndromes, such as acute coronary syndrome and heart failure, which develop over many decades and represent the end result of several pathophysiological mechanisms. More precise disease classification and greater understanding of individual variations in disease pathology could drive the development of targeted therapeutics. Success in designing clinical trials for personalized medicine will require the selection of patient populations with attributes that can be targeted or that predict outcome, and the use of appropriate enrichment strategies once such attributes are identified. Here, we describe examples of personalized medicine in cardiovascular disease, discuss its impact on clinical trial design, and provide insight into the future of personalized cardiovascular medicine from a regulatory perspective.

Dosing recommendations for pharmacogenetic interactions related to drug metabolism.

OBJECTIVE: Pharmacogenomic studies have established the important contribution of drug-metabolizing enzyme genotype toward drug toxicity and treatment failure; however, clinical implementation of pharmacogenomics has been slow. The aim of this study was to systematically review the information on drug-metabolizing enzyme pharmacogenomics available in the US drug labeling, practice guidelines, and recommendations. METHODS: Drug-metabolizing enzyme genotype and phenotype information was assessed in US FDA drug labeling, clinical practice guidelines, and independent technology assessors to evaluate the consistency in information sources for healthcare providers. RESULTS: Eighty four gene-drug pairs were identified as having drug-metabolizing enzyme genotype or phenotype information within the label. The manner in which pharmacogenomic information was presented was heterogeneous both within the label and between clinical practice recommendations. CONCLUSION: For proper implementation of pharmacogenomics in clinical practice, information sources for healthcare providers should relay consistent and clear information for the appropriate use of biomarkers.

Identification of Stevens-Johnson syndrome and toxic epidermal necrolysis in electronic health record databases.

BACKGROUND: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) carry a high mortality risk. While identifying clinical and genetic risk factors for these conditions has been hindered by their rarity, large electronic health databases hold promise for identifying large numbers of cases for study, especially with the introduction in 2008 of ICD-9 codes more specific for these conditions. OBJECTIVE: The objective of this study is to estimate the validity of ICD-9 codes for ascertaining SJS/TEN in 12 collaborating research units in the USA, covering almost 60 million lives. METHODS: From the electronic databases at each site, we ascertained potential cases of SJS/TEN using ICD-9 codes. At five sites, a subset of medical records was abstracted and standardized criteria applied by board-certified dermatologists to adjudicate diagnoses. Multivariate logistic regression was used to identify factors independently associated with validated SJS/TEN cases. RESULTS: A total of 56 591 potential cases of SJS/TEN were identified. A subset of 276 charts was selected for adjudication and 39 (of the 276) were confirmed as SJS/TEN. Patients with the ICD-9 codes introduced after 2008 were more likely to be confirmed as cases (OR 3.32; 95%CI 0.82, 13.47) than those identified in earlier years. Likelihood of case status increased with length of hospitalization. Applying the probability of case status to the 56 591 potential cases, we estimated 475-875 to be valid SJS/TEN cases. CONCLUSION: Newer ICD-9 codes, along with length of hospitalization, identified patients with a high likelihood of SJS/TEN. This is important for identification of subjects for future pharmacogenomics studies.

Response-guided telaprevir therapy in prior relapsers? The role of bridging data from treatment-naïve and experienced subjects.

The purpose of this report is to illustrate the US Food and Drug Administration's rationale for approving response-guided therapy (RGT) for telaprevir (TVR) in combination with pegylated interferon-α and ribavirin (P/R) for the treatment of adults with genotype 1 chronic hepatitis C who were prior relapsers. RGT was prospectively evaluated in two registration trials of treatment-naïve subjects. In these studies, RGT allowed subjects who achieved undetectable hepatitis C virus RNA from weeks 4 and 12, known as extended rapid virologic response (eRVR), to stop all treatments at 24 weeks. A patient without eRVR received an additional 36 weeks of P/R after 12 weeks of a TVR triple regimen (total of 48 weeks). However, RGT in prior P/R relapsers was not prospectively evaluated. Empirical cross-trial data indicated high sustained virologic response rates (>90%) in prior relapsers achieving eRVR, irrespective of P/R duration (24 or 48 weeks). Further analyses demonstrated that interferon responsiveness does not change in P/R-experienced subjects with a second round of P/R. The comparability in interferon responsiveness across treatment courses allowed us to bridge data between treatment-naïve and P/R-experienced subjects to support the approval of RGT in prior relapse subjects.

Assessment of Dosing Strategies for Pediatric Drug Products.

Pediatric drug dosing is challenged by the heterogeneity of developing physiology and ethical considerations surrounding a vulnerable population. Often, pediatric drug dosing leverages findings from the adult population; however, recent regulatory efforts have motivated drug sponsors to pursue pediatric-specific programs to meet an unmet medical need and improve pediatric drug labeling. This paradigm is further complicated by the pathophysiological implications of obesity on drug distribution and metabolism and the roles that body composition and body size play in drug dosing. Therefore, we sought to understand the landscape of pediatric drug dosing by characterizing the dosing strategies from drug products recently approved for pediatric indications identified using FDA Drug Databases and analyze the impact of body size descriptors (age, body surface area, weight) on drug pharmacokinetics for several selected antipsychotics approved in pediatric patients. Our review of these pediatric databases revealed a dependence on body size-guided dosing, with 68% of dosing in pediatric drug labelings being dependent on knowing either the age, body surface area, or weight of the patient to guide dosing for pediatric patients. This dependence on body size-guided dosing drives the need for special consideration when dosing a drug in overweight and obese patients. Exploratory pharmacokinetic analyses in antipsychotics illustrate possible effects of drug exposure when applying different dosing strategies for this class of drugs. Future efforts should aim to further understand the pediatric drug dosing and obesity paradigm across pediatric age ranges and drug classes to optimize drug development and clinical care for this patient population.

Impact of TCF7L2 single nucleotide polymorphisms on hydrochlorothiazide-induced diabetes.

OBJECTIVE: Thiazide diuretics have been associated with increased risk for new onset diabetes (NOD), but pharmacogenetic markers of thiazide-induced NOD are not well studied. Single nucleotide polymorphisms (SNPs) in the transcription factor 7-like 2 gene (TCF7L2) represent the strongest and most reproducible genetic associations with diabetes. We investigated the association of tag SNPs in TCF7L2 with thiazide-induced NOD. METHODS: We identified cases that developed NOD and age, sex, and race/ethnicity-matched controls from the INternational VErapamil SR-Trandolapril STudy (INVEST). INVEST compared cardiovascular outcomes between two antihypertensive treatment strategies in ethnically diverse patients with hypertension and coronary artery disease. We genotyped 101 TCF7L2 tag SNPs and used logistic regression to test for pharmacogenetic (SNP×hydrochlorothiazide treatment) interactions. Permuted interaction P values were corrected with the PACT test and adjusted for diabetes-related variables. RESULTS: In INVEST whites, we observed three TCF7L2 SNPs with significant SNP×treatment interactions for NOD. The strongest pharmacogenetic interaction was observed for rs7917983 [synergy index 3.37 (95% CI 1.72-6.59), P=5.0×10, PACT=0.03], which was associated with increased NOD risk in hydrochlorothiazide-treated patients [odds ratio 1.53 (1.04-2.25), P=0.03] and decreased NOD risk in non hydrochlorothiazide-treated patients [odds ratio 0.48 (0.27-0.86), P=0.02]. The TCF7L2 SNP rs4506565, previously associated with diabetes, showed a similar, significant pharmacogenetic association. CONCLUSION: Our results suggest that hydrochlorothiazide treatment is an environmental risk factor that increases diabetes risk beyond that attributed to TCF7L2 variation in white, hypertensive patients. Further study and replication of our results is needed to confirm pharmacogenetic influences of TCF7L2 SNPs on thiazide-induced NOD.

The functional G143E variant of carboxylesterase 1 is associated with increased clopidogrel active metabolite levels and greater clopidogrel response.

INTRODUCTION: Carboxylesterase 1 (CES1) is the primary enzyme responsible for converting clopidogrel into biologically inactive carboxylic acid metabolites. METHODS: We genotyped a functional variant in CES1, G143E, in participants of the Pharmacogenomics of Anti-Platelet Intervention (PAPI) study (n=566) and in 350 patients with coronary heart disease treated with clopidogrel, and carried out an association analysis of bioactive metabolite levels, on-clopidogrel ADP-stimulated platelet aggregation, and cardiovascular outcomes. RESULTS: The levels of clopidogrel active metabolite were significantly greater in CES1 143E-allele carriers (P=0.001). Consistent with these findings, individuals who carried the CES1 143E-allele showed a better clopidogrel response as measured by ADP-stimulated platelet aggregation in both participants of the PAPI study (P=0.003) and clopidogrel-treated coronary heart disease patients (P=0.03). No association was found between this single nucleotide polymorphism and baseline measures of platelet aggregation in either cohort. CONCLUSION: Taken together, these findings suggest, for the first time, that genetic variation in CES1 may be an important determinant of the efficacy of clopidogrel.

A Multistakeholder Perspective on Advancing Individualized Therapeutics.

Precision medicine has evolved from the application of pharmacogenetic biomarkers to the prospective development of targeted therapies in patients with specific molecular/genetic subtypes of disease to truly "N-of-1" medicines targeted to very small numbers of patients - in some cases, a single identified patient. This latter iteration of precision medicine presents unprecedented opportunities for patients with severe, life-threatening, or life-limiting diseases. At the same time, these modalities present complex scientific, clinical, and regulatory challenges. To realize the promise of individualized medicines, a multistakeholder approach to streamlining medical diagnoses, advancing the technologies that enable development of these therapeutic modalities, and re-envisioning collaborative environments for access and evidence generation is of critical importance. Herein, we highlight some of these challenges and opportunities.

Model-Informed Approach Supporting Approval of Nexviazyme (Avalglucosidase Alfa-ngpt) in Pediatric Patients with Late-Onset Pompe Disease.

In August 2021, the US Food and Drug Administration approved Nexviazyme (avalglucosidase alfa-ngpt) for intravenous infusion to treat patients 1 year of age and older with late-onset Pompe disease (LOPD). The effectiveness and safety were studied in patients with LOPD and patients with infantile-onset Pompe disease (IOPD). The dosage(s) tested in clinical trials was 20 mg/kg every other week (qow) in patients with LOPD and 20 mg/kg and 40 mg/kg qow in patients with IOPD. While patients 3 years old and greater with LOPD were eligible for participation in the pivotal trial, the youngest patient enrolled was 16 years old. Therefore, pediatric patients with LOPD were not well represented in the clinical trial. The prevalence of LOPD in pediatrics is extremely low. Thus, conducting a clinical trial in pediatric patients with LOPD would be challenging. Given the similar pathophysiology, mechanism of action, and disease manifestations across the age spectrum of patients with LOPD, the approved dosages for pediatric patients younger than 16 years old with LOPD were based on extrapolation of efficacy using a model-informed exposure bridging strategy, leveraging the safety data from pediatric patients with IOPD. Specifically, the exposure associated with 20 mg/kg qow in adult patients with LOPD was the target exposure for bridging of efficacy. The safety data obtained with 40 mg/kg qow in patients with IOPD was leveraged to support approval in pediatric patients with LOPD aged 1 year and older. This article illustrates a regulatory use of model-informed extrapolation approach for dose selection in pediatric patients with a rare disease.

Dose selection for biological enzyme replacement therapy indicated for inborn errors of metabolism.

This paper summarizes key features of the dose-finding strategies used in the development of 11 approved new molecular entities that are first-in-class enzyme replacement therapy (ERT), with a goal to gain insight into the dose exploration approaches to inform efficient dose-finding in future development of biological products for Inborn Errors of Metabolism (IEM). Dose exploration should preferably begin in in vitro studies, followed by testing multiple doses in an appropriate animal disease model, when available, which can provide important information for dose assessment in humans. Performing adequate dose-finding in early phase clinical studies in a well-defined study population, including pediatric subjects, is generally critical to inform dose selection for pivotal trials; alternatively, additional dose exploration can be incorporated as part of a pivotal trial. Two important considerations for successful dose selection include (1) identifying appropriate disease-specific endpoints, including pharmacodynamic (PD) end points and intermediate clinical end points or clinical end points, and (2) designing a study with adequate treatment durations for evaluating these end points. Appropriately selected PD biomarkers is useful for dose selection, and early development of these biomarkers can facilitate the overall clinical development program. Optimization of ERT doses, as well as evaluations of patient intrinsic factors and/or immune tolerance strategies may be necessary to overcome antibody responses or increase efficacy in IEM.

Dose-finding studies in drug development for rare genetic diseases.

BACKGROUND: The small patient populations inherent to rare genetic diseases present many challenges to the traditional drug development paradigm. One major challenge is generating sufficient data in early phase studies to inform dose selection for later phase studies and dose optimization for clinical use of the drug. However, optimizing the benefit-risk profile of drugs through appropriate dose selection during drug development is critical for all drugs, including those being developed to treat rare diseases. Recognizing the challenges of conducting dose finding studies in rare disease populations and the importance of dose selection and optimization for successful drug development, we assessed the dose-finding studies and analyses conducted for drugs recently approved for rare genetic diseases. RESULTS: Of the 40 marketing applications for new molecular entity (NME) drugs and biologics approved by the United States Food and Drug Administration for rare genetic diseases from 2015 to 2020, 21 (53%) of the development programs conducted at least one dedicated dose-finding study. In addition, the majority of drug development programs conducted clinical studies in healthy subjects and included population pharmacokinetic and exposure-response analyses; some programs also conducted clinical studies in patient populations other than the disease for which the drug was initially approved. The majority of primary endpoints utilized in dedicated dose-finding studies were biomarkers, and the primary endpoint of the safety and efficacy study matched the primary endpoint used in the dose finding study in 9 of 13 (69%) drug development programs where primary study endpoints were assessed. CONCLUSIONS: Our study showed that NME drug development programs for rare genetic diseases utilize multiple data sources for dosing information, including studies in healthy subjects, population pharmacokinetic analyses, and exposure-response analyses. In addition, our results indicate that biomarkers play a key role in dose-finding studies for rare genetic disease drug development programs. Our findings highlight the need to develop study designs and methods to allow adequate dose-finding efforts within rare disease drug development programs that help overcome the challenges presented by low patient prevalence and other factors. Furthermore, the frequent reliance on biomarkers as endpoints for dose-finding studies underscores the importance of biomarker development in rare diseases.

Expanding Approved Patient Populations for Rare Disease Treatment Using In Vitro Data.

In vitro cell-based data can be used to support the extension of pharmaceutical approval to patient subsets with unique genetic variants. A set of conditions should be satisfied to support the extension of approval. The disease mechanism should be well described, and the impact of variants on protein function should be reasonably understood. The incidence data should show that clinical trials for the variants in question are not practical. The overall safety and efficacy of the drug should be clear in adequate and well-controlled clinical trials. The clinical trial should include patients found to be responders and nonresponders so that both positive and negative predictive power of the in vitro assay may be measured. The mechanism of action of the drug should be clearly defined and should be consistent with the disease mechanism. The assay system should be qualified, including the following points: (i) each variant construct should be confirmed by bidirectional sequencing; (ii) the in vitro assay should directly measure the variant protein function in comparison with the reference protein; (iii) the assay should be formally validated to the extent possible, clearly demonstrating precision, reproducibility, and sensitivity used to support the efficacy claim; and (iv) the primary data should be available for inspection and analytical validation. The overall goal is a robust and validated cell-based system that can be shown to predict the outcome of targeted therapy.

Model-Informed Approach Supporting Drug Development and Regulatory Evaluation for Rare Diseases.

A rare disease is defined as a condition affecting fewer than 200 000 people in the United States by the Orphan Drug Act. For rare diseases, it is challenging to enroll a large number of patients and obtain all critical information to support drug approval through traditional clinical trial approaches. In addition, over half of the population affected by rare diseases are children, which presents additional drug development challenges. Thus, maximizing the use of all available data is in the interest of drug developers and regulators in rare diseases. This brings opportunities for model-informed drug development to use and integrate all available sources and knowledge to quantitatively assess the benefit/risk of a new product under development and to inform dosing. This review article provides an overview of 4 broad categories of use of model-informed drug development in drug development and regulatory decision making in rare diseases: optimizing dose regimen, supporting pediatric extrapolation, informing clinical trial design, and providing confirmatory evidence for effectiveness. The totality of evidence based on population pharmacokinetic simulation as well as exposure-response relationships for efficacy and safety, provides the regulatory ground for the approval of an unstudied dosing regimen in rare diseases without the need for additional clinical data. Given the practical and ethical challenges in drug development in rare diseases, model-informed approaches using all collective information (eg, disease, drug, placebo effect, exposure-response in nonclinical and clinical settings) are powerful and can be applied throughout the drug development stages to facilitate decision making.