Natsoft has expertise in developing and offering products & services to the Pharma and Biotech companies. Our Clinical Trial Intelligence platform provides a premier enterprise solution for both Pharma and Biotech companies to accelerate clinical trial design and approval of new novel cancer drugs. Our Machine Learning, AI and RPA (Robotic Process Automation) capabilities are increasing the process efficiencies and reducing the Drug Development time for our clients.

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.

European and U.S. clinical trial data transparency initiatives -- such as EMA Policy 70 -- are creating additional disclosure compliance requirements for pharma and biotech companies. These transparency initiatives have, at their core, the distribution of clinical trial data for public consumption. Clinical trial data typically are contained within regulatory documents such as Clinical Study Reports (CSRs), Marketing Application Submission Documents (NDAs, MAAs, BLAs, etc.) and others. To achieve compliance with these mandates, pharma and biotech companies will need to anonymize and de-identify data sets in their clinical study reports and submission documents, produce research summaries suitable for a lay audience, and publish their clinical study information publicly. In this webinar, Synchrogenix President, Keith Kleeman will discuss how Artificial Intelligence (AI) and natural language recognition and processing are significantly improving the accuracy and efficiency of successfully anonymizing personally identifiable information, patient protected data, company confidential information and other sensitive information from clinical trial documents for public disclosure.