Co-Development of Oncology Drugs and Companion Diagnostics: Analyses of Approval Lags and Drug Development Periods in Recently Approved Cases in Japan.

BACKGROUND: The utilization of biomarkers has become increasingly active to enhance efficiency of clinical development. This study evaluated the current situation and quantitative impact of co-development of companion diagnostics (CDx) on the oncology drug development in Japan. METHODS: Based on publicly available information about the oncology drugs and CDx approved in Japan in 2010-2020, we evaluated the approval lag time between drugs and CDx, and the duration between the pivotal study start date and the new drug application submission date (the time to application). Influences of multiple factors including the use of CDx on the time to application were also analyzed. RESULTS: A diagnostic test was mostly used from an early development phase such as phase1/2 study, and the median approval lag has tended to decrease when approved CDx were used (- 507 vs. - 25 days for newly developed CDx). The shorter median times to application were observed in Drugs with CDx (1204 days) compared to Targeted therapies without CDx (1423 days) or Other drugs without CDx (1853 days), although both the cancer types and the implementation of multi-regional clinical trials have a larger impact on the time to application compared to the use of CDx. CONCLUSIONS: The use of CDx from the early development phase and the global development strategy could have a positive contribution on the development period of oncology drugs, which will facilitate patients' earlier access to the optimal treatment.

Automated segmentation of articular disc of the temporomandibular joint on magnetic resonance images using deep learning.

Temporomandibular disorders are typically accompanied by a number of clinical manifestations that involve pain and dysfunction of the masticatory muscles and temporomandibular joint. The most important subgroup of articular abnormalities in patients with temporomandibular disorders includes patients with different forms of articular disc displacement and deformation. Here, we propose a fully automated articular disc detection and segmentation system to support the diagnosis of temporomandibular disorder on magnetic resonance imaging. This system uses deep learning-based semantic segmentation approaches. The study included a total of 217 magnetic resonance images from 10 patients with anterior displacement of the articular disc and 10 healthy control subjects with normal articular discs. These images were used to evaluate three deep learning-based semantic segmentation approaches: our proposed convolutional neural network encoder-decoder named 3DiscNet (Detection for Displaced articular DISC using convolutional neural NETwork), U-Net, and SegNet-Basic. Of the three algorithms, 3DiscNet and SegNet-Basic showed comparably good metrics (Dice coefficient, sensitivity, and positive predictive value). This study provides a proof-of-concept for a fully automated deep learning-based segmentation methodology for articular discs on magnetic resonance images, and obtained promising initial results, indicating that the method could potentially be used in clinical practice for the assessment of temporomandibular disorders.

Phase I study of ipatasertib as a single agent and in combination with abiraterone plus prednisolone in Japanese patients with advanced solid tumors.

PURPOSE: Ipatasertib is a selective inhibitor of Akt, a frequently activated protein kinase in human cancers. The current study assessed the safety, tolerability, and pharmacokinetics of ipatasertib in Japanese patients with solid tumors. METHODS: This was a phase I, open-label, 3 + 3 dose-escalation study conducted in two stages. In stage I, Japanese patients with solid tumors were administered ipatasertib 200, 400, or 600 mg/day for 21 days of a 28-day cycle. In stage II, Japanese patients with castration-resistant prostate cancer were administered ipatasertib 200 or 400 mg/day in combination with abiraterone and prednisolone in 28-day cycles. Dose-limiting toxicity (DLT) was assessed at each dose before enrolling patients at a higher dose; DLT was used to determine the maximum tolerated dose (MTD) and maximum administered dose (MAD). Pharmacokinetic parameters were assessed after a single dose and at steady state. RESULTS: Fifteen patients were enrolled in Stage I and six in Stage II. The ipatasertib MTD was 600 mg as monotherapy and MAD was 400 mg in combination with abiraterone and prednisolone. Ipatasertib plasma exposure was dose proportional across the dose range, and was not markedly affected by concurrent administration of abiraterone plus prednisolone. Stable disease (SD) was observed in eight patients treated with ipatasertib monotherapy (53.3%); four patients had SD and one had complete response with ipatasertib plus abiraterone and prednisolone. CONCLUSIONS: Ipatasertib, at the monotherapy MTD of 600 mg/day and MAD of 400 mg/day in combination with abiraterone and prednisolone, was safe and tolerable in Japanese patients with solid tumors.