INDUSTRY
PHARMACEUTICALS
Identifying Patients for Clinical Trial
There is major incentive for drug companies to reduce R&D spending, both to free up funds for additional ventures as well as to be able to offer lower prices for their products.
Machine learning, and AI can help introduce efficiencies to the clinical trial process in two ways. First, by more quickly and precisely identifying patients who would be a good fit for a particular trial via advanced analysis of medical records through natural language processing (NLP) or by exploring geographically- and symptom-distinct patients at scale avoiding later challenges, side effects and potential complications.
The estimated cost for drug development by U.S. biopharmaceutical companies is nearly $ 1 billion per drug. Pharmaceutical companies can leverage machine learning techniques to not only cull through literature and journal publications but also to pre-screen for the most effective potential compounds to prioritize their time.
GxP Compliance for Pharmaceuticals: A collaborative effort
The pharmaceutical industry’s highly regulatory environment can be tremendously demanding for organizations navigating the space. One of the biggest concerns that the pharmaceutical industry constantly attempts to address is the safety of its products and integrity of data used to make product-related safety decisions, a concern aimed to be addressed by GxP, a collection of regulations for good practices used in pharmaceuticals.
We help our customers, working with some cutting edge tools and technologies to achieve customer needs.
Leveraging analytics & AI to scale initiatives
The regulatory environment has become more challenging, demanding and far more extensive, testing, before drugs can go to market.
Pre-processing data usually involves deconstructing the data into words or chunks of words (tokenization), removing parts of speech without any inherent meaning (like stop words such as a, the, an), making the data more uniform (like changing all words to lowercase), and grouping words into pre-defined categories such as the names of persons (entity extraction). Manually, this process can take an inordinate amount of time, but we use some of the best industry tools to achieve the same.