Dr. Murakami from Pharmacology BU to present at the symposium of the 99th Annual Meeting of the Japanese Pharmacological Society

2026.03.09

Dr. Murakami from the Pharmacology Business Unit, will deliver an oral presentation at The 99th Annual Meeting of the Japanese Pharmacological Society, to be held in Kawauchi Campus, Tohoku University, Japan.
If you plan to attend the conference, we encourage you to join the session and hear the presentation.

Conference Name:The 99th Annual Meeting of the Japanese Pharmacological Society

Date & Time: March 16 (Mon), 2026, 14:10-15:40 (JST)

Location: Kawauchi Campus, Tohoku University, Japan, Symposium 12

Title: Uncovering Hidden Dimensions of Behavior: Drug-Induced Behavioral Changes in Model Animals

Presentation Summary
In drug discovery research, particularly in the field of central nervous system (CNS) disorders, animal behavior is widely used as an important endpoint for compound evaluation. Conventional approaches typically rely on analyzing a single behavioral parameter using experienced researchers or specialized software. To capture more subtle and multidimensional behavioral changes induced by compounds, we are advancing the development of a comprehensive behavioral evaluation platform leveraging artificial intelligence (AI). Using a schizophrenia model, we are conducting multidimensional behavioral analyses following administration of clinically used drugs, with the aiming to identify digital parameters that correlate with clinical symptoms. Data acquisition and analysis are ongoing, and we will present interim findings at this conference. We also aim to discuss how the concept of phenomics—which allows comprehensive and hypothesis-free characterization of behavioral phenotypes—may broaden the future framework of behavioral evaluation in drug discovery research.

Axcelead DDP’s Soulution
At Axcelead, we are collaborating with Revamp Corporation, which specializes in AI-based behavioral analysis systems, to build a digital behavioral analysis platform. This system enables detection of behavioral patterns that are difficult or impossible to identify by human observation alone, as well as the identification of digital parameters that correlate with clinical symptoms. Through this approach, we aim to enhance compound value creation and accelerate drug development. As this platform can be applied not only to CNS disorders but also to a wide range of therapeutic areas, please feel free to contact us if you are facing challenges in behavioral pharmacology studies or digital phenotyping analysis.