Today, technologies like artificial intelligence (AI) have impacted the daily lives of people in many ways. For example, Alexa can give the news headlines or thermostats knowing more about the whereabouts and travel plans. Therefore, it is clear that AI will immensely change the world in many ways, which might not anticipate. In recent years, the life science industry is also implementing AI in their businesses to benefit from it.
Many AI-based devices have already proved their advantages in the life science and healthcare sector. The image analytics are utilized in the pharma researcher for describing the features of the cell lines as they want to understand the disease mechanisms and efficiency of the drug candidate. Furthermore, text analytics is used for identifying adverse events in advance. Several organizations are also using innovative techniques to find ways that will help them repurpose drugs.
Although some complicated and niche applications are further behind in innovation, the tools’ competency is increasing rapidly.
Such a wide range of capability and rapid transformation might make it difficult to estimate when and where to implement AI, but its potential is clear. For example, scientists can use artificial intelligence to navigate complicated and massive amounts of data in life science. They can evaluate the full range of chemical compounds for discovering the next life-changing drugs. AI can also be used for matching the accurate patient for clinical trials as it can recognize the patients who require extra support to remain engaged throughout the execution of the trail.
However, AI is a term that can be interpreted differently, and it depends upon the perspective. Most of the time, terms like machine learning, deep learning, and AI are used interchangeably and mostly to create marketing hype. Therefore, such inconsistent utilization of the term develops communication challenges among the people who want to understand and benefit from artificial intelligence.
4 Ways AI Is Transforming Life Sciences:
Life sciences experts see significant potential for artificial intelligence to enhance healthcare. A recent survey found that 90 percent of life sciences’ firms recognized AI as essential in driving innovation and achieving outcomes. Firms are recognizing that AI has begun to make huge inroads to life sciences, be it discovering huge biological data using machine learning, combining health records and genomic data, discovering new drugs, making the diagnosis, or customizing health procedures as in precision medicine. The following are the areas where the life science industry uses AI effectively.
• Advancing Diagnostics
Histopathology image analysis and automated diagnosis are the best matches for AI, given the technological progress in the digitalization of complete histology slides, which allow all microscopic magnifications. AI, combined with complex algorithms and automated immunohistochemical measurement systems, has advanced pathologists’ potential to oversee the analysis and concentrate on more complex cases.
• Research of New Products
Life sciences firms explore how AI can be leveraged to identify indications for existing products or research new candidates.
Using advanced learning algorithms to mine real-world structured and unstructured data to unleash insights can lead to the identification of new mechanisms of disease, new line extension, and design for pre-clinical experiments.
• Accelerating Drug Development
Across the industry, product development range several years from discovery to launch. Advancements in AI can reduce the time it takes to develop, manufacture, and launch new therapies to support the goal of reducing overall product development timelines. Scientists are combining research data, lab data, and clinical data, combined with information sources across the drug development spectrum, creating a holistic picture of the drug development.
• Driving Compliance
Compliance is a burden on companies and needs an approach to mitigate costs while meeting regulation. While automation tools are available, many do not satisfy the accuracy required to meet the policy’s demands. New AI applications are emerging, utilizing advanced algorithms based on customized NLP technologies and text-mining models. Using advanced models, it is possible to FIND keywords, phrases, and data patterns that may require anonymization.