AION Labs creates AI startup to increase success of drug candidates
According to AION Labs, OMEC.AI will develop AI-based technology to analyze preclinical data to then identify potential gaps in efficacy and safety to improve the probability of success of drug candidates in clinical trials.
The first challenge for OMEC will be to create the computational platform necessary to find these weaknesses in drug candidates. Once this has been achieved, the team states that the program will be able to suggest experiments to address these shortcomings.
AION will provide the startup with pharmaceutical data for model training and advanced machine learning development to progress the creation of the platform.
AION itself is formed of a variety of pharmaceutical companies, including AstraZeneca, Merck KGaA, Pfizer, and Teva, which operate alongside other stakeholders, such as Amazon and the Israel Biotech Fund.
The organization was launched in October 2021 with the aim of creating and investing in early-stage startup companies focused on AI and computational biology in drug discovery and development.
OMEC represents the first startup to be funded by the collaboration. The startup will be led by Ori Shachar and Amir Harel, who had previously worked with Mobileye – an Israeli technology company focused on autonomous driving technology that was bought by Intel in 2017.
"There is currently no automated solution that employs all preclinical data in a way that allows a reliable assessment of the clinical trial readiness of a drug candidate. We are aiming to fill this gap," stated Shachar, co-founder and CEO of OMEC.
The startup outlined that it will work with ‘omic’ technology. This technology is aimed at the universal detection of genes, mRNA, protein, and metabolites in a biological sample through the analysis of large amounts of data.
Such an approach is already used in preclinical studies. However, OMEC states that they are unreliable in predicting human biology, and it is the startup’s goal to make the process a more reliable assessment of a drug candidate’s likelihood of success in clinical studies.
The use of AI to actively discover and develop drug candidates has advanced significantly in recent years, with the first entirely AI developed drug progressed into clinical trials in 2020.
As the pandemic gripped the world and research became difficult to organize, this also led to an increasing reliance on this technology to bolster drug discovery, with 37% of respondents in a survey saying that COVID-19 had accelerated adoption of AI. The research also showed that 77% of life science business leaders are using AI within their organization.
