Chronic obstructive pulmonary disease (COPD) remains a leading cause of death worldwide, yet only one new drug class has been approved in the last decade. However, resurgence in COPD treatment has been recently fueled by a greater understanding of the pathophysiology and natural history of the disease, as well as a growing prevalence and an aging population. Currently, there are nearly 25 novel drug targets in development. Furthermore, the indication has undergone some fundamental changes over the last couple of years, including an updated diagnosis paradigm, validation, and approval of patient-reported outcome questionnaires for clinical trials, and drug development tools, such as a prognostic biomarker for patient selection. In the context of clinical trials, this review aims to summarize recent changes to the diagnosis and evaluation of COPD and to provide an overview of US and European regulatory guidance.

The diagnosis and management of drug-induced liver injury (DILI) remains a challenge in clinical trials in drug development. The qualification of emerging biomarkers capable of predicting DILI soon after the initiation of treatment, differentiating DILI from underlying liver disease, identifying the causal entity, and assigning appropriate treatment options after DILI is diagnosed are needed. Qualification efforts have been hindered by lack of properly stored and consented biospecimens that are linked to clinical data relevant to a specific context of use. Recommendations are made for biospecimen collection procedures, with the focus on clinical trials, and for specific emerging biomarkers to focus qualification efforts.

We improved a previous pharmacological target adverse-event (TAE) profile model to predict adverse events (AEs) on US Food and Drug Administration (FDA) drug labels at the time of approval. The new model uses more drugs and features for learning as well as a new algorithm. Comparator drugs sharing similar target activities to a drug of interest were evaluated by aggregating AEs from the FDA Adverse Event Reporting System (FAERS), FDA drug labels, and medical literature. An ensemble machine learning model was used to evaluate FAERS case count, disproportionality scores, percent of comparator drug labels with a specific AE, and percent of comparator drugs with the reports of the event in the literature. Overall classifier performance was F1 of 0.71, area under the precision-recall curve of 0.78, and area under the receiver operating characteristic curve of 0.87. TAE analysis continues to show promise as a method to predict adverse events at the time of approval.

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.

Trastuzumab deruxtecan (T-DXd) is a HER2-targeting antibody-drug conjugate composed of a novel enzyme-cleavable linker and membrane-permeable topoisomerase I inhibitor payload. T-DXd has been approved for HER2-positive metastatic breast cancer and for HER2-positive metastatic gastric cancer. The approval in breast cancer was based on results from the DESTINY-Breast01 (U201; NCT03248492) and J101 (NCT02564900) trials. Here, we present dose justification for the approved 5.4 mg/kg every-3-weeks (Q3W) dose based on exposure-efficacy evaluated in patients with HER2-positive breast cancer (N = 337) from these 2 trials. Exposure-safety was assessed in patients with all tumor types (N = 639, n = 512 with breast cancer) across 5 trials, including J101 and DESTINY-Breast01. T-DXd doses ranged from 0.8-8.0 mg/kg Q3W; most patients received 5.4 (n = 312) or 6.4 mg/kg (n = 291). For each end point, multivariate logistic or Cox regression analysis was performed using various exposure metrics of T-DXd and released drug. A statistically significant association was observed between intact T-DXd area under the concentration-time curve (AUC) and confirmed objective response rate (ORR; P = 0.028). No significant exposure-response relationships were observed between intact T-DXd or released drug and duration of response or progression-free survival; however, follow-up was limited. All evaluated safety end points demonstrated a significant (P < 0.05) relationship with either intact T-DXd or released drug, with higher adverse event (AE) rates projected at higher exposures. Dose-response projections suggested an increase in ORR (67.5% vs. 62.9%) and toxicity (e.g., grade ≥ 3 all-cause treatment-emergent AEs: 61% vs. 54%) with T-DXd 6.4 vs. 5.4 mg/kg. Results demonstrate the benefit-risk profile at different doses and guide clinicians in the use of the 5.4-mg/kg Q3W dose in patients with HER2-positive metastatic breast cancer.

For the development of coronavirus disease 2019 (COVID-19) drugs during the ongoing pandemic, speed is of essence whereas quality of evidence is of paramount importance. Although thousands of COVID-19 trials were rapidly started, many are unlikely to provide robust statistical evidence and meet regulatory standards (e.g., because of lack of randomization or insufficient power). This has led to an inefficient use of time and resources. With more coordination, the sheer number of patients in these trials might have generated convincing data for several investigational treatments. Collaborative platform trials, comparing several drugs to a shared control arm, are an attractive solution. Those trials can utilize a variety of adaptive design features in order to accelerate the finding of life-saving treatments. In this paper, we discuss several possible designs, illustrate them via simulations, and also discuss challenges, such as the heterogeneity of the target population, time-varying standard of care, and the potentially high number of false hypothesis rejections in phase II and phase III trials. We provide corresponding regulatory perspectives on approval and reimbursement, and note that the optimal design of a platform trial will differ with our societal objective and by stakeholder. Hasty approvals may delay the development of better alternatives, whereas searching relentlessly for the single most efficacious treatment may indirectly diminish the number of lives saved as time is lost. We point out the need for incentivizing developers to participate in collaborative evidence-generation initiatives when a positive return on investment is not met.

Global regulatory agencies have transformed their approach to approvals in their processes for formal review of the safety and efficacy of new drugs. Opportunities for innovation have expanded because of the coronavirus disease 2019 (COVID-19) pandemic. Several regulatory-led initiatives have progressed rapidly during the past year, including patient-focused drug development, model-informed drug development, real-world evidence, and complex innovative trial designs. Collectively, these initiatives have accelerated the rate of approvals. Despite demands to focus on urgent needs imposed by the COVID-19 pandemic, the number of new drug approvals over the past year, particularly for rare diseases, has outpaced expectations. Advancing therapeutics for nervous system disorders requires adaptive strategies that align with rapid developments in the field. Three relentlessly progressive diseases, amyotrophic lateral sclerosis, Duchenne muscular dystrophy, and Parkinson's disease are in urgent need of new treatments. Herein, we propose new regulatory initiatives, including innovative trial designs and patient-focused drug development that accelerate clinical trial conduct while meeting critical regulatory requirements for therapeutic approval.

To address unresolved questions about drug safety and efficacy at the time of approval, the European Medicines Agency (EMA) may require that manufacturers conduct additional studies during the postmarketing period. As a growing proportion of new cancer drugs are approved on the basis of limited evidence of clinical benefit, timely completion of postmarketing requirements is important. We used publicly available regulatory documents to evaluate key characteristics of pivotal studies supporting EMA-approved cancer drugs from 2004-2014 and assessed completion rates of postmarketing data collection requirements after a minimum of 5 years. From 2004-2014, 79% (45/57) of EMA-approved cancer drugs had to fulfill postmarketing requirements. Pivotal trials supporting the approval of cancer drugs with postmarketing requirements were less likely to have randomized designs (41/61, 67% vs. 11/11, 100%), include an active comparator (20/61, 33% vs. 10/11, 91%), or measure overall survival as the primary study end point (18/61, 30% vs. 6/11, 55%) compared with pivotal trials for drugs without postmarketing requirements. Among 200 postmarketing requirements, almost half were designed to assess drug safety. After a minimum of 5 years, 60% (121/200) of requirements were completed, 10% (19/200) were ongoing, and 30% (60/200) were delayed. About half (40/75, 53%) of postmarketing requirements for new clinical studies were completed on time. Delays in the completion of postmarketing requirements often did not impact the likelihood of drugs receiving permanent marketing authorization (87%, 39/45) after 5 years. Our findings highlight the need for EMA to better enforce its authority to require timely completion of postmarketing requirements and studies.

Ubrogepant is a novel, oral calcitonin gene-related peptide receptor antagonist currently under US Food and Drug Administration (FDA) review for the acute treatment of migraine attacks. This double-blind, four-period crossover study compared the cardiac repolarization effect of therapeutic (100 mg) and supratherapeutic (400 mg) ubrogepant doses vs. placebo in healthy adults. Moxifloxacin 400 mg was used as an open-label active control, and the primary end point was change from baseline in Fridericia-corrected QT intervals (ΔQTcF). Assay sensitivity was demonstrated via statistically significant QTcF prolongation with moxifloxacin vs. placebo. After single oral doses of ubrogepant, the least squares mean placebo-corrected ΔQTcF (ΔΔQTcF) and 90% confidence intervals (CIs) did not exceed the 10-millisecond regulatory threshold at any timepoint. The 90% CI upper bounds were 2.46 milliseconds and 2.69 milliseconds for ubrogepant 100 and 400 mg, respectively. Categorical and concentration-based analyses were consistent with the primary result, showing no significant impact of ubrogepant on cardiac repolarization.

Compassionate use is a system that provides patients with exceptional access to investigational new drugs to treat life-threatening diseases that have no effective conventional treatments. The purpose of this study was to characterize and assess the current status of the compassionate use program's application in Japan by evaluating expanded access clinical trials (EACTs) conducted between 2016 and 2021. In this study, a data set containing all EACTs, and pivotal clinical trials (PCTs) conducted in Japan between February 2016 and April 2021 was obtained from the Pharmaceutical and Medical Devices Agency, systemically reviewed, and analyzed. During the 5 years since EACTs began in Japan, out of 2,031 PCTs, 31 EACTs were conducted in Japan. Twenty-four trials (77.4%) of the 31 EACTs used anticancer drugs and 5 of those trials (16.1%) were conducted in children. Furthermore, we conducted an EACT survey for drugs with a high degree of social and patient demands as recommended in the EACT notification. Among the 2,031 PCTs, we found 152 trials with high degree of social and patient demands. Of these, EACT was implemented in 17 trials (11.2%). Days from the start of the EACT to the submission of new drug applications and the approval were 9.0 (67.0-56.5) and 208.0 (172.8-308.8) days, respectively. Of the 31 EACTs conducted, 24 (77.4%) drugs have been approved as of August 2021. This first comprehensive study on EACTs clarified the current status and issues of Japan's compassionate use system and the 5 years since the program initiated.

Extended-release (XR) formulations enable less frequent dosing vs. conventional (e.g., immediate release (IR)) formulations. Regulatory registration of such formulations typically requires pharmacokinetic (PK) and clinical efficacy data. Here we illustrate a model-informed, exposure-response (E-R) approach to translate controlled trial data from one formulation to another without a phase III trial, using a tofacitinib case study. Tofacitinib is an oral Janus kinase (JAK) inhibitor for the treatment of rheumatoid arthritis (RA). E-R analyses were conducted using validated clinical endpoints from phase II dose-response and nonclinical dose fractionation studies of the IR formulation. Consistent with the delay in clinical response dynamics relative to PK, average concentration was established as the relevant PK parameter for tofacitinib efficacy and supported pharmacodynamic similarity. These evaluations, alongside demonstrated equivalence in total systemic exposure between IR and XR formulations, provided the basis for the regulatory approval of tofacitinib XR once daily by the US Food and Drug Administration.

The B-cell receptor signaling pathway, which is critical to the development and maturation of normal B-cells, is emerging as an attractive therapeutic target in B-cell malignancies. Ibrutinib is a potent irreversible inhibitor of Bruton's tyrosine kinase (Btk), a key kinase important for signal transduction in the B-cell receptor (BCR) pathway. In preclinical studies, ibrutinib potently bound to Btk, inhibited BCR signaling, and decreased tumor cell proliferation and survival in many B-cell malignancy models. Excellent safety and efficacy data in clinical trials have led to US Food and Drug Administration (FDA) approval of ibrutinib for previously treated mantle cell lymphoma (MCL) and chronic lymphocytic leukemia (CLL), as well as CLL with 17p deletion. Ongoing clinical studies have also demonstrated great potency of ibrutinib in treating other types of non-Hodgkin's lymphoma (NHL), including diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and Waldenström's macroglobulinemia (WM). Combination of ibrutinib with chemoimmunotherapy and other promising novel agents in B-cell malignancy therapy has also been under clinical investigation.

Several antiepileptic drugs (AEDs) have US Food and Drug Administration (FDA) approval for use as mood stabilizers in bipolar disorder (BD), but not all BD patients respond to these AED mood stabilizers (AED-MSs). To identify genetic polymorphisms that contribute to the variability in AED-MS response, we performed a discovery genome-wide association study (GWAS) of 199 BD patients from the Mayo Clinic Bipolar Disorder Biobank. Most of these patients had been treated with the AED-MS valproate/divalproex and/or lamotrigine. AED-MS response was assessed using the Alda scale, which quantifies clinical improvement while accounting for potential confounding factors. We identified two genome-wide significant single-nucleotide polymorphism (SNP) signals that mapped to the THSD7A (rs78835388, P = 7.1E-09) and SLC35F3 (rs114872993, P = 3.2E-08) genes. We also identified two genes with statistically significant gene-level associations: ABCC1 (P = 6.7E-07; top SNP rs875740, P = 2.0E-6), and DISP1 (P = 8.9E-07; top SNP rs34701716, P = 8.9E-07). THSD7A SNPs were previously found to be associated with risk for several psychiatric disorders, including BD. Both THSD7A and SLC35F3 are expressed in excitatory/glutamatergic and inhibitory/γ-aminobutyric acidergic (GABAergic) neurons, which are targets of AED-MSs. ABCC1 is involved in the transport of valproate and lamotrigine metabolites, and the SNPs in ABCC1 and DISP1 with the strongest evidence of association in our GWAS are strong splicing quantitative trait loci in the human gut, suggesting a possible influence on drug absorption. In conclusion, our pharmacogenomic study identified novel genetic loci that appear to contribute to AED-MS treatment response, and may facilitate precision medicine in BD.

The increasing availability of genotype data linked with information about drug-response phenotypes has enabled genomewide association studies (GWAS) that uncover genetic determinants of drug response. GWAS have discovered associations between genetic variants and both drug efficacy and adverse drug reactions. Despite these successes, the design of GWAS in pharmacogenomics (PGx) faces unique challenges. In this review, we analyze the last decade of GWAS in PGx. We review trends in publications over time, including the drugs and drug classes studied and the clinical phenotypes used. Several data sharing consortia have contributed substantially to the PGx GWAS literature. We anticipate increased focus on biobanks and highlight phenotypes that would best enable future PGx discoveries.

Acetaminophen (paracetamol-APAP) is the most common cause of drug-induced liver injury in the Western world. Reactive metabolite production by cytochrome P450 enzymes (CYP-metabolites) causes hepatotoxicity. We explored the toxicokinetics of human circulating APAP metabolites following overdose. Plasma from patients treated with acetylcysteine (NAC) for a single APAP overdose was analyzed from discovery (n = 116) and validation (n = 150) patient cohorts. In the discovery cohort, patients who developed acute liver injury (ALI) had higher CYP-metabolites than those without ALI. Receiver operator curve (ROC) analysis demonstrated that at hospital presentation CYP-metabolites were more sensitive/specific for ALI than alanine aminotransferase (ALT) activity and APAP concentration (optimal CYP-metabolite receiver operating characteristic area under the curve (ROC-AUC): 0.91 (95% confidence interval (CI) 0.83-0.98); ALT ROC-AUC: 0.67 (0.50-0.84); APAP ROC-AUC: 0.50 (0.33-0.67)). This enhanced sensitivity/specificity was replicated in the validation cohort. Circulating CYP-metabolites stratify patients by risk of liver injury prior to starting NAC. With development, APAP metabolites have potential utility in stratified trials and for refinement of clinical decision-making.

We describe here the design and initial implementation of the eMERGE-PGx project. eMERGE-PGx, a partnership of the Electronic Medical Records and Genomics Network and the Pharmacogenomics Research Network, has three objectives: (i) to deploy PGRNseq, a next-generation sequencing platform assessing sequence variation in 84 proposed pharmacogenes, in nearly 9,000 patients likely to be prescribed drugs of interest in a 1- to 3-year time frame across several clinical sites; (ii) to integrate well-established clinically validated pharmacogenetic genotypes into the electronic health record with associated clinical decision support and to assess process and clinical outcomes of implementation; and (iii) to develop a repository of pharmacogenetic variants of unknown significance linked to a repository of electronic health record-based clinical phenotype data for ongoing pharmacogenomics discovery. We describe site-specific project implementation and anticipated products, including genetic variant and phenotype data repositories, novel variant association studies, clinical decision support modules, clinical and process outcomes, approaches to managing incidental findings, and patient and clinician education methods.

Antiplatelet response to clopidogrel shows wide variation, and poor response is correlated with adverse clinical outcomes. CYP2C19 loss-of-function alleles play an important role in this response, but account for only a small proportion of variability in response to clopidogrel. An aim of the International Clopidogrel Pharmacogenomics Consortium (ICPC) is to identify other genetic determinants of clopidogrel pharmacodynamics and clinical response. A genomewide association study (GWAS) was performed using DNA from 2,750 European ancestry individuals, using adenosine diphosphate-induced platelet reactivity and major cardiovascular and cerebrovascular events as outcome parameters. GWAS for platelet reactivity revealed a strong signal for CYP2C19*2 (P value = 1.67e-33). After correction for CYP2C19*2 no other single-nucleotide polymorphism reached genomewide significance. GWAS for a combined clinical end point of cardiovascular death, myocardial infarction, or stroke (5.0% event rate), or a combined end point of cardiovascular death or myocardial infarction (4.7% event rate) showed no significant results, although in coronary artery disease, percutaneous coronary intervention, and acute coronary syndrome subgroups, mutations in SCOS5P1, CDC42BPA, and CTRAC1 showed genomewide significance (lowest P values: 1.07e-09, 4.53e-08, and 2.60e-10, respectively). CYP2C19*2 is the strongest genetic determinant of on-clopidogrel platelet reactivity. We identified three novel associations in clinical outcome subgroups, suggestive for each of these outcomes.