Pioneering Pharma Blockchain AI for Drug Development

Integrating blockchain with life science/pharmaceutical applications will decentralize the interface and data exchange, resulting in high efficiency, greater speeds, low marginal cost, and infinite scalability.

Pioneering Pharma Blockchain AI for Drug Development

Integrating blockchain with life science/pharmaceutical applications will decentralize the interface and data exchange, resulting in high efficiency, greater speeds, low marginal cost, and infinite scalability.

EntelMed was established to develop broad capabilities across 3 segments:

EntelMed was established to develop broad capabilities across 3 segments:

Pharma Blockchains AI for Drug Development

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.

Pharma Blockchains AI for Drug Development

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.

Quantum Computing in Drug Discovery

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.

Clinical Trial Management

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.

Quantum Computing in Drug Discovery

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.

Clinical Trial Management

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.

Current State of Clinical Trials

Ongoing research has shown that drug development costs continue to rise with an average of 9% each year. Unfortunately, drug development speed, costs, and success rates have not improved over the years, and in some instances, operating conditions have worsened. This has resulted in a situation where success rates for new candidate medicinal products entering clinical development are at an all-time low, with only 11% ultimately making it to the market.

Blockchain Opportunities

Clinical research generates enormous amounts of trial data daily, increasing the pressures on regulatory agencies to overcome such significant data barriers. Besides, it is becoming evident that legacy data management systems are not strong enough to process and preserve the data extracted from current research studies. These systems lack relevant measures to build trust in the clinical trial industry among consumers and regulators.

Mission

Use the power of EntelMed scientific and development innovation to create advanced technologies that benefit more patients, sooner.

Vision

Build a world class pharma blockchain AI R&D capability to conceive and develop life-changing technologies for patients.