Clinical Pharmacology & Therapeutics最新文献

Accurate clinical translation of preclinical research remains challenging, primarily due to species-specific differences and disease and patient heterogeneity. An important recent advancement has been development of microphysiological systems that consist of multiple human cell types that recapitulate key characteristics of their respective human systems, allowing essential physiologic processes to be accurately assessed during drug development. However, an unmet need remains regarding a quantitative method to evaluate the similarity between diverse sample types for various contexts of use (CoU)-specific pathways. To address this gap, this study describes the development of pathway-based similarity measurement (PBSM), which leverages RNA-seq data and pathway-based information to assess the human relevance of preclinical models for specific CoU. PBSM offers a quantitative method to compare the transcriptomic similarity of preclinical models to human tissues, shown here as proof of concept for liver and cardiac tissues, enabling improved model selection and validation. Thus, PBSM can successfully support CoU selection for preclinical models, assess the impact of different gene sets on similarity calculations, and differentiate among various in vitro and in vivo models. PBSM has the potential to reduce the translational gap in drug development by allowing quantitative evaluation of the similarity of preclinical models to human tissues, facilitating model selection, and improving understanding of context-specific applications. PBSM can serve as a foundation for enhancing the physiological relevance of in vitro models and supporting the development of more effective therapeutic interventions.

Implementation of pharmacogenetic testing in clinical care has been slow and with few exceptions is hindered by the lack of real-world evidence on how to best target testing. In this retrospective register-based study, we analyzed a nationwide cohort of 1,425,000 patients discharged from internal medicine or surgical wards and a cohort of 2,178 university hospital patients for purchases and prescriptions of pharmacogenetically actionable drugs. Pharmacogenetic variants were obtained from whole genome genotype data for a subset (n = 930) of the university hospital patients. We investigated factors associated with receiving pharmacogenetically actionable drugs and developed a literature-based cost-benefit model for pre-emptive pharmacogenetic panel testing. In a 2-year follow-up, 60.4% of the patients in the nationwide cohort purchased at least one pharmacogenetically actionable drug, most commonly ibuprofen (25.0%) and codeine (19.4%). Of the genotyped subset, 98.8% carried at least one actionable pharmacogenetic genotype and 23.3% had at least one actionable gene-drug pair. Patients suffering from musculoskeletal or cardiovascular diseases were more prone to receive pharmacogenetically actionable drugs during inpatient episode. The cost-benefit model included frequently dispensed drugs in the university hospital cohort, comprising ondansetron (19.4%), simvastatin (7.4%), clopidogrel (5.0%), warfarin (5.1%), (es)citalopram (5.3%), and azathioprine (0.5%). For untargeted pre-emptive pharmacogenetic testing of all university hospital patients, the model indicated saving €17.49 in direct healthcare system costs per patient in 2 years without accounting for the cost of the test itself. Therefore, it might be reasonable to target pre-emptive pharmacogenetic testing to patient groups most likely to receive pharmacogenetically actionable drugs.

Vincristine (VCR) can cause vincristine-induced peripheral neuropathy (VIPN) during the treatment of acute lymphoblastic leukemia (ALL) and the mechanisms are complicated. The aim of this study was to investigate the influencing factors on the population pharmacokinetics (PopPK) and pharmacodynamics (PD) related to VIPN, including clearance routes, drug-drug interactions (DDI), and genetic characteristics. Pediatric patients being treated for ALL were recruited to PK study where VCR and its metabolite (M1) were measured using a novel assay. The incidence of VIPN was also recorded. DNA sequencing of relevant PK and PD genes was performed. PopPK and PK/PD models were developed, pharmacogenetic and DDI analyses were conducted. In total, 79 children were recruited. The results showed that allometric scaling, ABCB1-rs1128503 genotype, and posaconazole (POS) significantly improved the PopPK model fit. VIPN was significantly correlated with the exposure of VCR. Co-administration with POS shifted the effect curve for VIPN to the left, indicating increased VIPN risk at the same exposure levels. No significant effects on VIPN were observed for CYP3A5 (rs776746), CYP3A4 (rs2242480), CEP72 (rs924607), or various ABCB1 variants (rs1128503, rs2032582, rs1045642, rs4728709, rs4148737, and rs10276036), nor with the co-administration of fluconazole or dasatinib. In summary, co-administration of POS increased VCR exposure by 0.4-fold and raised the risk of VIPN, with an occurrence probability generally exceeding 0.7. Therapeutic drug monitoring of VCR in clinical practice may be necessary to enable appropriate dose adjustments and individualized treatment.

Saroglitazar magnesium, a dual PPAR α/γ agonist, currently in Phase III for treating primary biliary cholangitis (PBC), was evaluated for its pharmacokinetic (PK) profile, safety, and pharmacodynamics in participants with cholestatic liver disease (CLD) across different levels of hepatic impairment (HI) and participants with severe renal impairment (RI). Three PK studies comparing saroglitazar with healthy controls were conducted: Study 1 involved daily oral doses of 1 or 2 mg for 4 weeks in 12 PBC cirrhosis participants with mild or moderate HI; Study 2 assessed single-dose PK (2 or 4 mg) in eight non-cirrhotic CLD participants; Study 3 evaluated single-dose PK (2 mg) in eight participants with severe RI. On day 1, saroglitazar exposure increased by 14.6-42% in mild HI vs. normal, but by day 28, levels were similar, indicating no accumulation. In moderate HI, exposure was significantly increased by 50.4-85% on days 1 and 28, with 34-46% lower clearance despite a similar half-life. The moderate HI group had a 59% higher exposure than the non-cirrhotic group. Saroglitazar (1 and 2 mg) reduced alkaline phosphatase (ALP) levels by 17-40% after 4 weeks in participants with abnormal baseline ALP. Single-dose PK in non-cirrhotic CLD (2 and 4 mg) and severe RI (2 mg) was comparable to matched controls without significant safety issues. Overall, saroglitazar (1 and 2 mg) was safe and well-tolerated in cholestatic cirrhosis with mild HI and participants with severe RI without major PK changes. Moderate HI increased exposure and decreased clearance without any safety concerns.

Recently, a new type of drug lag, known as "drug loss" has emerged in Japan. It is a condition where the development of a drug approved in other countries has not been initiated in Japan. For 265 new drugs approved in the United States or Europe during 2010-2020, only 31% had commenced development in Japan as of December 31, 2020. A characteristic feature of Japanese guidelines on new drug development is that, in principle, clinical trial data in Japanese participants are required in each study phase. Given key players in new drug development are shifting from large pharmaceutical companies to emerging biopharma companies, primarily based outside Japan, the necessity for Japanese data may contribute to the drug lag. This study aimed to clarify the guideline adherence to new drug applications in Japan. Of the 159 new drugs approved in Japan between April 2019 and March 2024, the clinical data packages for almost all drugs included both pharmacokinetic (PK) data and efficacy and safety data in Japanese participants, irrespective of the study phase or design. We identified three flexible development approaches: the absence of Japanese dose-response data (39.6%), absence of Japanese confirmatory data generated from phase III randomized controlled trials (35.2%), and post-hoc Japanese PK data (43.0%, 34/79). Biologics, orphan drug designation, antineoplastic agents, and same applicant and originator were identified as factors significantly associated with these flexibilities. The results will help foreign companies, including emerging biopharmas, in formulating effective new drug development strategies, potentially alleviating the drug lag in Japan.

Psychedelics have recently re-emerged as potential treatments for various psychiatric conditions that impose major public health costs and for which current treatment options have limited efficacy. At the same time, personalized medicine is increasingly being implemented in psychiatry to provide individualized drug dosing recommendations based on genetics. This review brings together these topics to explore the utility of pharmacogenomics (a key component of personalized medicine) in psychedelic-assisted therapies. We summarized the literature and explored the potential implications of genetic variability on the pharmacodynamics and pharmacokinetics of psychedelic drugs including lysergic acid diethylamide (LSD), psilocybin, N,N-dimethyltryptamine (DMT), 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT), ibogaine and 3,4-methylenedioxymethamphetamine (MDMA). Although existing evidence is limited, particularly concerning pharmacodynamics, studies investigating pharmacokinetics indicate that genetic variants in drug-metabolizing enzymes, such as cytochrome P450, impact the intensity of acute psychedelic effects for LSD and ibogaine, and that a dose reduction for CYP2D6 poor metabolizers may be appropriate. Furthermore, based on the preclinical evidence, it can be hypothesized that CYP2D6 metabolizer status might contribute to altered acute psychedelic experiences with 5-MeO-DMT and psilocybin when combined with monoamine oxidase inhibitors. In conclusion, considering early evidence that genetic factors can influence the effects of certain psychedelics, we suggest that pharmacogenomic testing should be further investigated in clinical research. This is necessary to evaluate its utility in improving the safety and therapeutic profile of psychedelic therapies and a potential future role in personalizing psychedelic-assisted therapies, should these treatments become available.

The trough concentration (C₀) of tacrolimus in children with nephrotic syndrome (NS) has rarely been explored, so its target level was based on transplant research. This study aimed to determine the optimal tacrolimus C₀ in NS children. Data from primary NS children treated with tacrolimus at Wuhan Children's Hospital in the last 10 years were retrospectively collected. According to the cutoff C₀ analyzed by receiver-operator characteristics (ROC) analysis, patients were divided into very low- (< 4 ng/mL), low- (4-5 ng/mL), medium- (5-7 ng/mL), and high-concentration (7-10 ng/mL) groups. A total of 196 patients were enrolled for primary outcome analysis. Compared to medium-concentration group, only the very low-concentration group obtained significant inferior primary outcomes, including overall remission rate, relapse-free survival rate, and relapse rate at 6 months. For secondary outcomes, the very low-concentration group experienced more frequent treatment failure in 12 months, whereas the high-concentration group suffered a higher risk of adverse events than the medium-concentration group. For steroid-resistant NS, very low- and low-concentration groups required longer time to achieve remission compared to medium-concentration group. For steroid-sensitive NS, the very low-concentration group suffered a higher relapse frequency than medium-concentration group. Lastly, the dose of tacrolimus required for children with different CYP3A5 genotypes with or without Wuzhi capsules was analyzed. In conclusion, tacrolimus may be targeted to C₀ of 4-7 ng/mL during the first 6 months in children with NS. For steroid-resistant NS, C₀ of 5-7 ng/mL can achieve a rapid remission.

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.

Rare diseases, affecting millions globally, present significant drug development challenges. This is due to the limited patient populations and the unique pathophysiology of these diseases, which can make traditional clinical trial designs unfeasible. Quantitative Systems Pharmacology (QSP) models offer a promising approach to expedite drug development, particularly in rare diseases. QSP models provide a mechanistic representation of the disease and drug response in virtual patients that can complement routinely applied empirical modeling and simulation approaches. QSP models can generate digital twins of actual patients and mechanistically simulate the disease progression of rare diseases, accounting for phenotypic heterogeneity. QSP models can also support drug development in various drug modalities, such as gene therapy. Impactful QSP models case studies are presented here to illustrate their value in supporting various aspects of drug development in rare indications. As these QSP model applications continue to mature, there is a growing possibility that they could be more widely integrated into routine drug development steps. This integration could provide a robust framework for addressing some of the inherent challenges in rare disease drug development.