Leveraging AI will not only enhance the possibility of early discoveries and diagnosis but also result in a significant reduction in the timeline for drug development and increased market opportunities.
FREMONT, CA: Artificial intelligence (AI) aims to assist humans in tasks that traditionally depend on human intelligence. The use of AI in the biotech and pharma industry has reinforced how scientists design new drugs, tackle the disease, and much more.
Before the incorporation of AI in the industry, scientists spent more time on lower cognitive tasks such as collecting the data that may help in decision-making to reach a hypothesis or discover an accurate and important theory. AI can manage to reach invaluable insights within a few hours, something that the researchers spent weeks doing. With the adoption of big data analytics tools and AI by the pharmaceutical industry, validating theories, generating hypotheses, finding unexpected targets, and biomarkers are becoming faster and easier.
AI technologies will assist pharma in several ways. Huge volumes of thesis and publications can be analyzed within a span of a few minutes using computer vision. With complex connections between pathways, drugs, diseases, and genes can be visualized using image-recognition techniques. Such medical images can be read to gather accurate hypotheses and diagnoses over different indications with sentiment analysis. Unforeseen side effects can also be mapped out. Thus personalized medicine can finally be possible with machine learning (ML).
An AI program that uses deep-learning algorithms accurately identified 95 percent of skin cancers from a set of images compared with 86.6 percent accuracy from 58 dermatologists who examined the same images. The program will be crucial in the detection of early-stage skin cancers, thereby benefitting millions of people. AI can be helpful in the creation of such useful tools whose adoption should be strongly encouraged. Leveraging AI will not only enhance the possibility of early discoveries and diagnosis but also result in a significant reduction in the timeline for drug development and increased market opportunities.
Using AI, pharma and life sciences industries will enable more accurate and faster real-time insights into understanding the trending topics, market scenario, and unmet requirements of patients, visualizing huge volumes of patient, medical, and scientific data, and much more.
Despite favorable usefulness of AI in the life sciences and pharmaceutical industries, not every company has completely adopted cutting-edge technology. According to Accenture, the estimated potential savings were $150 billion from the US healthcare economy alone by 2026 using AI-based clinical health applications. Moreover, the study stated that almost 20 percent of untapped clinical demands would be addressed using AI.
The pharma industry requires high R&D expenses, long drug development timelines, and 9 out of 10 failed clinical experiments. Amidst such challenges, even minor enhancements are worth pursuing. Establishment of a strong AI strategy can result in breakthrough disruptor the industry is expecting in the 21st century.