Biomedical industry is accustomed to lengthy cycle time, high cost and low success rate of new drug development. Because of AI-guided drug development, a new horizon of development is opened for drug research and development which may eventually resolve the conflict in conventional drug development.

AI combines machine learning, natural language processing, big data and other technology in all areas of the pharmaceutical industry to dramatically improve the efficiency and quality of new drug development, decrease the chance of clinical failure, and cut R&D costs.

Reducing R&D Costs

The greatest benefit of AI-based drug development is that research and development costs will significantly be reduced. Traditional drug discovery has to go through target identification, molecular synthesis, drug screening, clinical trials, etc, resulting in very expensive.

AI, by contrast, can deep-learn from a mass of data about drugs already in use to deconstruct the chemical composition and biological activity of drugs, develop new ones more efficiently, and model elaborate mechanisms of absorption, metabolism and toxicity. Through simplifying the discovery and development process for new drugs, AI lowers enterprises' research and development costs, increasing drug R&D success rates and ROI.

Accelerating Time-to-Market

For the traditional method, the average time from inception to launch for a new drug is over 10 years (due to several phases of research, development and testing).

AI can use sophisticated machine calculation and simulations to process large scale chemical and biological data (like compounds' structure and mechanism of action), quickly and precisely identify targets, filter the finest compound molecules, and estimate their pharmacokinetic and toxicological effects. So AI-guided drug discovery and development could greatly reduce the time of cycle for all drug discovery and preclinical development activities.

Case Studies

There are a huge number of case studies that have demonstrated AI-guided drug development as a major advance over conventional pharmaceuticals in new drug research and development. What we can see is that companies that have employed AI in drug discovery have reported that screening best-fit drug candidates for further development via AI not only saves money but also helps with success.

Real-World Impact

As new drugs take much less time to develop and commercialize - which makes AI-guided therapies more cost-effective for patients. Particularly for conditions for which no available cure exists so far, AI-guided screening of novel compounds and repurposing of drugs that are already in use are of significant importance in altering the treatment outcome.

Overall, AI-empowering can help bring drug research and development to a far lower cost and risk, as well as substantially improve research and development efficiency. In the future, as AI gets more integrated into the pharmaceutical world, AI-assisted drug discovery and development is likely to become the new paradigm of novel drug discovery and development. To remain in the pharmaceutical race or if you're a startup trying to make your mark, adding AI to your R&D platform early isn't just an option, it's a strategic must.

At Protheragen MedAI, we understand the special power of AI in pharma and that is why we provide pharmaceutical companies with leading AI models and tools for defending human health. Interested in our services? Please contact us.