With advanced AI and machine learning technologies, biopharma can work together to help make their goals reality, build a better business, and make people healthier.
FREMONT, CA: Lifesciences is no strangers to rapid disruption. Although there is a high level of innovation in the industry, biopharma companies face a challenging environment due to increased competition and R&D cycle times. Technologies, especially Artificial Intelligence (AI), could provide a lifeline to biopharma research and development and help companies reverse this trend. Here is how AI-enabled transformation is helping biopharma companies.
Life sciences companies are discovering how AI can be leveraged to identify new indications for existing products or research new candidates. Using sophisticated AI algorithms to mine real-world structured and unstructured data to unleash insights can lead to identifying new mechanisms of disease, potential line extension, and design for preclinical experiments. Ai can also help fill knowledge gaps in how candidates act on proteins to aid the design of new drugs.
Data can be extracted in real-time from the commercial, scientific, and regulatory environment, enabling researchers to find competitive white space, avoid blind spots in research, and discover disease similarities.
Across the life sciences industry, product development timelines is several years from discovery to launch. Advancements in AI can significantly reduce the time it takes to develop, manufacture, and launch new patient therapies to support the goal of mitigating overall product development timelines. Researchers are integrating research data, lab data, and clinical data, combined with new information sources across the drug development spectrum, developing a holistic picture of the drug development candidate. Enhancing ways to acquire and mine data in real-time allows researchers to use AI to make improved decisions faster, accelerating the product development and scale-up overall process.
AI represents a big opportunity for life sciences companies to radically transform business at all levels, including organization structures, processes, and people. However, an overall vision is needed to shape what firms want to accomplish. For this, companies need to think big, start small, and scale fast.