Exposure-safety analyses of nintedanib in patients with chronic fibrosing interstitial lung disease.

BACKGROUND: Nintedanib reduces the rate of decline in forced vital capacity in patients with idiopathic pulmonary fibrosis (IPF), other chronic fibrosing interstitial lung diseases (ILDs) with a progressive phenotype and systemic sclerosis-associated ILD (SSc-ILD). The recommended dose of nintedanib is 150 mg twice daily (BID). METHODS: Data from Phase II and III trials in IPF and Phase III trials in SSc-ILD and progressive fibrosing ILDs other than IPF were analyzed to investigate the relationship between nintedanib plasma concentrations (exposure) and safety (liver enzyme elevations [defined as transaminase elevations equal or greater than 3 times the upper limit of normal] and diarrhea). RESULTS: Using data from 1403 subjects with IPF treated with 50-150 mg nintedanib BID, a parametric time-to-first-event model for liver enzyme elevations was established. Besides exposure, gender was a significant covariate, with a three-fourfold higher exposure-adjusted risk in females than males. Subsequent analysis of combined data from IPF, SSc-ILD (n = 576) and progressive fibrosing ILD (n = 663) studies suggested a consistent exposure-liver enzyme elevation relationship across studies. No exposure-diarrhea relationship was found using data from the various fibrosing ILDs, but diarrhea risk was dependent on dose administered. CONCLUSIONS: The positive correlation between exposure and risk of liver enzyme elevations was consistent across nintedanib studies in IPF, SSc-ILD and progressing fibrosing ILDs other than IPF. The effect size does not warrant a priori dose adjustment in patients with altered plasma exposure (excluding hepatic impairment patients, where there are specific labelling recommendations). For diarrhea, dose administered was a better predictor than exposure.

Phase I dose-escalation and -expansion study of buparlisib (BKM120), an oral pan-Class I PI3K inhibitor, in patients with advanced solid tumors.

PURPOSE: The pan-Class I PI3K inhibitor buparlisib (BKM120) has shown activity in a range of preclinical cancer models. This first-in-man study was initiated to identify the maximum tolerated dose (MTD) of buparlisib (100 mg/day) and to assess safety and preliminary efficacy. METHODS: Patients with advanced solid tumors (N = 83) enrolled in a Phase I dose-escalation and -expansion study of single-agent buparlisib. Patients in the dose-expansion arm (n = 43) had tumor samples with PIK3CA and/or PTEN alterations. RESULTS: The most common cancers were colorectal (n = 31) and breast cancer (n = 21). Median number of prior antineoplastic regimens was four (range: 1-12). Grade 3/4 adverse events (AEs) included asthenia (12.0 %) and performance status decrease (9.6 %). Treatment-related AEs (all grades) included decreased appetite, diarrhea, nausea (each in 33 % of patients), hyperglycemia (31 %) and rash (29 %). One confirmed partial response (PR; triple-negative breast cancer) and three unconfirmed PRs (parotid gland carcinoma, epithelioid hemangiothelioma, ER + breast cancer) were reported. Tumor molecular status did not predict clinical benefit in the full study cohort, or among the colorectal or breast cancer subpopulations. Pharmacodynamic biomarkers ((18)F-FDG-PET, C-peptide, pS6) demonstrated dose-dependent changes; however, tumor heterogeneity precluded a clear correlation with clinical benefit. CONCLUSION: Buparlisib was well tolerated up to the 100 mg/day dose and showed preliminary activity in patients with advanced cancers. Future studies in more homogeneous patient populations will evaluate buparlisib in combination with other agents and further investigate the use of predictive biomarkers.

Pharmacokinetic-pharmacodynamic analysis of drug liking blockade by buprenorphine subcutaneous depot (CAM2038) in participants with opioid use disorder.

Buprenorphine is used to treat opioid use disorder (OUD). Weekly and monthly subcutaneous long-acting buprenorphine injections (CAM2038) provide more stable buprenorphine plasma levels and reduce the treatment burden, misuse, and diversion associated with sublingual transmucosal buprenorphine formulations. To characterize the pharmacokinetic/pharmacodynamic (PK/PD) relationship, a maximum inhibition (Imax) model was developed relating CAM2038 buprenorphine plasma concentration to drug liking maximum effect (Emax) visual analog scale (VAS; bipolar) score after intramuscular hydromorphone administration. Data included time-matched observations of buprenorphine plasma concentration and drug liking Emax VAS score after hydromorphone 18 mg administration in 47 non-treatment-seeking adults with moderate to severe OUD in a phase 2 study. Analysis used non-|linear mixed-effects modeling (NONMEM®). The final Imax model adequately described the PK/PD relationship between buprenorphine plasma concentration and drug liking Emax VAS score. Simulations showed drug liking was effectively blocked at low buprenorphine plasma concentrations (0.4 ng/mL) where the upper 95% confidence interval of the drug liking Emax VAS score was below the pre-defined 11-point complete blockade threshold. The buprenorphine plasma concentration required to achieve 90% of the maximal effect (IC90) of drug liking was 0.675 ng/mL. Interindividual variability in responses to buprenorphine was observed; some participants experienced fluctuating responses, and a few did not achieve drug liking blockade even with higher buprenorphine plasma concentrations. This affirms the need to individualize treatment and titrate doses for optimal treatment outcomes. PK/PD models were also developed for desire to use VAS and Clinical Opiate Withdrawal Scale (COWS) scores, with results aligned to those for drug liking.

How to Successfully Generate an Alternative Approach to a Thorough QT Study: GLPG1972 as an Example.

During development of a drug, the requirement of evaluating the proarrhythmic risk and delayed repolarization needs to be fulfilled. Would it be possible to create an alternative to a thorough QT (TQT) study or is there a need to perform a dedicated TQT study? How is an alternative approach generated, what information is available, and which instructions are considered missing today to generate such an approach? This tutorial describes the considerations and path followed to create an early and feasible alternative to a TQT study using experience-based insights from a successful application to the US Food and Drug Administration for GLPG1972, an ADAMTS-5 inhibitor, and discusses the approach used in light of the current guidelines and literature.

Dynamic tumor modeling of the dose-response relationship for everolimus in metastatic renal cell carcinoma using data from the phase 3 RECORD-1 trial.

BACKGROUND: The phase 3 RECORD-1 trial (NCT00410124) established the efficacy and safety of everolimus in patients with metastatic renal cell carcinoma (mRCC) who progress on sunitinib or sorafenib. In RECORD-1, patients received 10 mg everolimus daily, with dose reduction to 5 mg daily allowed for toxicity. We have developed a model of tumor growth dynamics utilizing serial measurements of the sum of the longest tumor diameters (SLD) from individual RECORD-1 patients to define the dose-response relationship of everolimus. RESULTS: The model predicts that after 1 year of continuous dosing, the change in SLD of target lesions will be +142.1% ± 98.3%, +22.4% ± 17.2%, and -15.7% ± 11.5% in the average patient treated with placebo, 5 mg everolimus, and 10 mg everolimus, respectively. This nonlinear, mixed-effects modeling approach can be used to describe the dynamics of each individual patient, as well as the overall population. This allows evaluation of how an actual dosing history and individual covariates impact on the observed drug effect, and offers the possibility of predicting clinical observations as a function of time. CONCLUSIONS: In this pharmacodynamic model of tumor response, everolimus more effectively shrinks target lesions in mRCC when dosed 10 mg daily versus 5 mg daily, although a 5-mg dose still shows an antitumor effect. These data support earlier studies that established 10 mg daily as the preferred clinical dose of everolimus, and improve our understanding of the everolimus dose-response relationship.

Open innovation: Towards sharing of data, models and workflows.

Sharing of resources across organisations to support open innovation is an old idea, but which is being taken up by the scientific community at increasing speed, concerning public sharing in particular. The ability to address new questions or provide more precise answers to old questions through merged information is among the attractive features of sharing. Increased efficiency through reuse, and increased reliability of scientific findings through enhanced transparency, are expected outcomes from sharing. In the field of pharmacometrics, efforts to publicly share data, models and workflow have recently started. Sharing of individual-level longitudinal data for modelling requires solving legal, ethical and proprietary issues similar to many other fields, but there are also pharmacometric-specific aspects regarding data formats, exchange standards, and database properties. Several organisations (CDISC, C-Path, IMI, ISoP) are working to solve these issues and propose standards. There are also a number of initiatives aimed at collecting disease-specific databases - Alzheimer's Disease (ADNI, CAMD), malaria (WWARN), oncology (PDS), Parkinson's Disease (PPMI), tuberculosis (CPTR, TB-PACTS, ReSeqTB) - suitable for drug-disease modelling. Organized sharing of pharmacometric executable model code and associated information has in the past been sparse, but a model repository (DDMoRe Model Repository) intended for the purpose has recently been launched. In addition several other services can facilitate model sharing more generally. Pharmacometric workflows have matured over the last decades and initiatives to more fully capture those applied to analyses are ongoing. In order to maximize both the impact of pharmacometrics and the knowledge extracted from clinical data, the scientific community needs to take ownership of and create opportunities for open innovation.