Acute graft-versus-host disease (aGVHD) following allogeneic hematopoietic cell transplantation (HCT) is a primary cause of nonrelapse mortality and a major barrier to successful transplant outcomes. Itacitinib is a Janus kinase (JAK)1-selective inhibitor that has demonstrated efficacy in preclinical models of aGVHD. We report results from the first registered study of a JAK inhibitor in patients with aGVHD. This was an open-label phase 1 study enrolling patients aged ≥18 years with first HCT from any source who developed grade IIB to IVD aGVHD. Patients with steroid-naive or steroid-refractory aGVHD were randomized 1:1 to itacitinib 200 mg or 300 mg once daily plus corticosteroids. The primary endpoint was safety and tolerability; day 28 overall response rate (ORR) was the main secondary endpoint. Twenty-nine patients (200 mg, n = 14; 300 mg, n = 15) received ≥1 dose of itacitinib and were included in safety and efficacy assessments. One dose-limiting toxicity was reported (grade 3 thrombocytopenia attributed to GVHD progression in a patient receiving 300 mg itacitinib with preexisting thrombocytopenia). The most common nonhematologic treatment-emergent adverse event was diarrhea (48.3%, n = 14); anemia occurred in 11 patients (38%). ORR on day 28 for all patients in the 200-mg and 300-mg groups was 78.6% and 66.7%, respectively. Day 28 ORR was 75.0% for patients with treatment-naive aGVHD and 70.6% in those with steroid-refractory aGVHD. All patients receiving itacitinib decreased corticosteroid use over time. In summary, itacitinib was well tolerated and demonstrated encouraging efficacy in patients with steroid-naive or steroid-refractory aGVHD, warranting continued clinical investigations. This trial was registered at www.clinicaltrials.gov as #NCT02614612.

Although traditional approaches to biomarker discovery have elucidated key molecular markers that have improved drug selection (precision medicine), the discovery of biomarkers that inform optimal dose selection (precision dosing) continues to be a challenge in many therapeutic areas. Larger and more diverse study populations are necessary to discover additional biomarkers that provide the resolution needed for a more tailored dose. To generate and accommodate large datasets of drug response phenotypes, time- and cost-efficient strategies are necessary. In particular, a multitude of technological advances that originated for purposes outside of biomedical research (electronic health records, direct-to-consumer genetic testing, social media, mobile devices, and machine learning) have made it easier to communicate, connect, and gather information from consumers. Although these technologies have been used with success in the health sciences for an array of purposes, these resources have not been fully capitalized on for precision dosing. This perspective will touch on how these innovations can be used as data sources, data collection tools, and data processing tools for drug-response phenotypes with a unique focus on advancing biomarker-driven precision dosing.

Sparse data exist on the penetration of antiretrovirals into brain tissue. In this work, we present a framework to use efavirenz (EFV) pharmacokinetic (PK) data in plasma, cerebrospinal fluid (CSF), and brain tissue of eight rhesus macaques to predict brain tissue concentrations in HIV-infected individuals. We then perform exposure-response analysis with the model-predicted EFV area under the concentration-time curve (AUC) and neurocognitive scores collected from a group of 24 HIV-infected participants. Adult rhesus macaques were dosed daily with 200 mg EFV (as part of a four-drug regimen) for 10 days. Plasma was collected at 8 time points over 10 days and at necropsy, whereas CSF and brain tissue were collected at necropsy. In the clinical study, data were obtained from one paired plasma and CSF sample of participants prescribed EFV, and neuropsychological test evaluations were administered across 15 domains. PK modeling was performed using ADAPT version 5.0 Biomedical Simulation Resource, Los Angeles, CA) with the iterative two-stage estimation method. An eight-compartment model best described EFV distribution across the plasma, CSF, and brain tissue of rhesus macaques and humans. Model-predicted median brain tissue concentrations in humans were 31 and 8,000 ng/mL, respectively. Model-predicted brain tissue AUC was highly correlated with plasma AUC (γ = 0.99, P < 0.001) but not CSF AUC (γ = 0.34, P = 0.1) and did not show any relationship with neurocognitive scores (γ < 0.05, P > 0.05). This analysis provides an approach to estimate PK the brain tissue in order to perform PK/pharmacodynamic analyses at the target site.