EntelMed’s strategy is to accelerate the drug discovery process by making it easier to identify promising compounds using blockchain, AI, and Quantum Computing.

Our initial objective involves an unprecedented volume of data, at least 10 million physical compounds, a minimum of 200 million activity data points collected in dose-response analyses, and more than a billion assay activity data points.
The value of pharmaceutical data has not been fully realized. EntelMed’s strategic objective is to develop technology to start to unlock that value. $2 Billion to Bring a Drug to Market

It takes 13 years and an average of almost $2 billion to bring a drug to market. It would benefit everyone, especially patients if we could become more efficient. The pharmaceutical industry has long been searching for a way to pool knowledge without compromising the confidentiality of their data.

To decrease the financial cost and chances of failure, pharmaceutical companies are shifting towards AI. We believe AI will revolutionize the pharmaceutical and medical sectors. Various pharmaceutical companies have made and continue investing in AI and have collaborated with AI companies to develop essential healthcare tools.

While Quantum Computing may benefit the entire pharma value chain—from research across production through commercial and medical—its primary value lies in R&D. Currently, pharma players process molecules with non-QC tools, such as MD and DFT, in a methodology called computer-assisted drug discovery (CADD). But the classical computers they rely on are sorely limited, and basic calculations predicting the behavior of medium-size drug molecules could take a lifetime to compute accurately.

EntelMed’s is planning to develop CADD on quantum computers that could increase the scope of biological mechanisms amenable to CADD, shorten screening time, and reduce the number of times an empirically based development cycle must be run by eliminating some of the research-related “dead ends,” which add significant time and cost to the discovery phase. QC-enhanced CADD would improve the development cycle. QC could make current CADD tools more effective by helping to predict molecular properties accurately.

With an electronic data capture (EDC), Blockchain tools allow clinical data to be automatically aggregated, replicated, and distributed among researchers and practitioners with greater auditability, provenance tracking, and control compared to complicated conventional systems.

Blockchain technology can improve clinical trials’ quality with better reproducibility and grant both researcher communities with secure data sharing and patient groups with tools guaranteeing their privacy. The smart contract is a decentralized application compared with other software types as it resides on the blockchain. The smart contract plays multiple roles, including automating an application’s business logic without the involvement of third parties, verifying the predetermined rules of operation, and enforcing obligations on an action if these rules are met.