sci-news.jpeg

sci-news

shimin.jpeg

shimin

eppharmaline.gif

eppharmaline

findat.jpeg

findat

yakuzemi.png

yakuzemi

new-lifescience.gif

new-lifescience

biopharmaceuticals.gif

biopharmaceuticals

jssx36.png

jssx36

convention.jpeg

convention

jshp2022-thk.png

jshp2022-thk

jasdi24.png

jasdi24

General information

Announcements(0)

Greetings from Chair

Overview

Registration

General information 2

Abstract Submission (Oral/Poster Presentation)

Program

Sessions

Search presentations

pharm142_en.png

Change account information such as the email address and password on the account setting screen common to Confit.

Login required to view

Password required to view

Presentation Information

Session Details

A password that applicants have been notified of is required to view abstracts. If you are a participant and need to confirm the password, please contact us by e-mail about which annual meeting you would like to know the password for to view abstracts. We will reply after confirming that you were a participant. Thank you for your understanding.

To browse or post comments, you must log in.

You cannot post comments as it is outside the comment posting period.

This comment has been deleted. You cannot reply to this comment.

Program Type

Announcements

Profile management

Bookmark

Download PDF for print

Timetable

Investigation on suicide-related adverse events associated with perampanel treatment utilizing adverse event reporting databases

We aim to gather researchers in the fields related to drug toxicity prediction by in silico methods, and to activate information exchanges for a research in this field in this symposium. Adverse drug reactions are serious factors for new drug candidates to drop out from the developing process. It is desired to control the risk of adverse drug reactions as well as the basic properties of drugs such as drug efficacy and physical in the early stages of drug development because the adverse drug reactions are the chemical toxic aspect of drugs. Therefore, it has been remarkable to use in silico method in recent years for quick and efficient evaluating of the risk of adverse drug reactions. In this symposium, we will introduce the developments of in silico methods for evaluating the toxicity and risk of adverse drug reactions, such as a machine learning and statistics prediction models using the existing databases related to pharmaceuticals or the in-house databases. Furthermore, we will discuss future prospects of studies in this field to establish evidences that the use of in silico methods is useful in accelerating drug development.

Prediction of drug toxicity by data-driven approach

The 142nd Annual Meeting of the Pharmaceutical Society of Japan (Nagoya)

Presentation Information

[GS01-1]Investigation on suicide-related adverse events associated with perampanel treatment utilizing adverse event reporting databases

Password required to view