Clinical trial drug attrition rate is disastrously at 93.1%. One of the reasons behind is the lack of pre-clinical safety assessment platform to predict common drug-induced adverse effects. Many drug-induced adverse effects, such as vomiting, are often unknown in pre-clinical stage, because common laboratory animals, like mice and rats do not vomit. These severe side effects only came into attention after entering human clinical trial, wasting a large amount of research funding and unexpected sufferings for volunteers participating in clinical trials. Many of the unexpected side effects are correlated to dysrhythmic and dysregulated electro-physiology. Bio-electrical data remains a highly-underutilized data resource that is seldom incorporated in drug discovery.  The current project therefore aims to give an example to the world to begin collecting and utilizing bio-electrical data resources to improve decision making in drug discovery.

We aim to create a world-unique and sustainable data resources collecting drug-induced changes in bio-electrical signal features using standardized protocol to comply a drug database. This first database we created focuses on the gut. Therefore, we named it GastroIntestinal Pacemaker Activity Drug Database (GIPADD).  Supported by our collaborators, the database will continue to grow with more datasets added and will be promoted to a larger beneficiaries after establishment. The database will allow drug-to-drug comparison and training of artificial intelligence to identify novel correlations and “electrical” biomarkers to improve decision making in drug discovery. These correlations may be further utilized into predicting drug-induced adverse effects, as well as predicting drug targets. Our final aim is to maximize drug therapeutic effects, and minimize unexpected drug adverse effects to improve quality of life in medical care in the general public.

To raise attention for the scientific communitie in creating dynamic and sustainable data resources to meet the current fast-growing digital and big-data era
To create new tools for drug discovery sectors to utilize bio-electrical data into hypothesis generation and decision making processes
To promote translational research, i.e. establishment of similar bio-electrical data resources
To promote establishment of standardized data resources to create high-quality data for artificial intelligence training
To bring together experts/companies who had been working on collecting, utilizing, and interpreting bio-electrical data together to strengthen this research area

• Research institutes and universities with projects related to drug discovery


• Pharmaceutical/Industrial partners


• Research sectors and multi-disciplinary research experts/ companies

2023

Healthcare, MedTech