Innoplexus announces an official partnership with ChemAxon, getting the most value out from life sciences data. Through the joint venture, Innoplexus will enable big pharma and biotech companies to find and connect information about pharmaceutical compounds from publicly available, or archived enterprise datasets to generate novel ideas. ChemAxon provides best-in-class solutions in cheminformatics for the chemistry, biotechnology, pharmaceutical, and agrochemical industries. Innoplexus, a global leader in artificial intelligence (AI) and blockchain for the life sciences industry, will leverage one of ChemAxon's products, ChemLocator, to search all potential, pre-clinical, clinical or marketed drugs in all documents across data assets in Innoplexus product, Ontosight, to detect industry-relevant signals much earlier than traditional methods. ChemLocator is a web-based search tool with chemical recognition capabilities that allows users to discover hidden chemical knowledge and extract structures from documents.

AI or Artificial Intelligence works by effectively combining high volumes of data using intelligent and quick algorithms with iterative processing and thereby allowing itself to self-learn automatically from the characteristics of such data. The applications and advantages of AI (Artificial Intelligence) are vast and involves many technologies and methods thereby. Machine learning is an application of artificial intelligence (AI) that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves. Machine learning has made possible AI based regulatory tools for managing risk and compliance and efficiently expedite life sciences research.

SAN FRANCISCO, CA – Late one evening, Gunjan Bhardwaj got a phone call from his friend and mentor -- a call that would change his career. Not long after, Bhardwaj spent days in the hospital, as his friend underwent painful chemotherapy. As a former consultant at Ernst and Young and Boston Consulting Group, Bhardwaj understood the flow of information in the Internet age. He knew artificial intelligence (AI) and machine learning were capable of digesting large data sets and arriving at powerful connections and insights. What Bhardwaj didn't understand was, why health-care information to help his friend wasn't available.

The increased use of artificial intelligence and machine learning is steadily shifting the paradigm of medical research and treatment, providing researchers real-time access to every white paper and clinical case study conducted on a genetic disorder. Being able to develop such an elaborate database of information allows researchers to not only understand the full scope of a medical condition, but further shorten the amount of time it takes to develop a cure. Founded in 2011, Innoplexus is a technology and product development company focused on solving complex challenges in the pharmaceutical and life sciences industries. Their end-to-end platform for Life Sciences research uses artificial intelligence to generate smart data and insights to assist in the discovery, clinical development and regulatory compliance of pharmaceutical medicine. On a mission to create self-service products that help enhance decision-making, their platform compiles hundreds of terabytes worth of scientific information spread across clinical trial databases, biological databases, major patent offices, forums and regulatory bodies.

As Kevin Rands, (a contributor at CIO.com) has stated in his blog "Data is the lifeline of any business", and truly said, it remains the heart of businesses for life sciences and pharmaceutical industries. A lot still relies upon data while conducting research which is mostly done through traditional methods. As many top notch business persons and influencers of the industry quote the importance of data and real-time information, use of such tools to provide solutions to these problems is still missing in the industry. A recent wave of innovation in analyzing the data and patterns is gaining prominence with the industry veterans, to come up with better solutions that are disrupting the data and analytics services. Slacking off the old and traditional methods to artificial intelligence and machine learning techniques would save up lots of research time amongst the life science professionals.