How AI accelerate drug development and opportunities
Traditional Drug Development
As biotech companies like $Pfizer(PFE)$ , $Amgen(AMGN)$ and $Gilead Sciences(GILD)$ are beginning to apply artificial intelligence and machine learning to drug development, potentially creating dozens of new drugs and a $50 billion market in the next decade, I think this breakthrough could be of value to both humans and investors. For biotech companies, the traditional process of developing and finding new drugs has been expensive and time-consuming. But now that artificial intelligence is on the rise, a new wave of drug development enabled by AI is helping companies use the vast amount of data to quickly identify patient responses and aim to develop viable drugs at a much lower cost and efficiency.
I think this could have implications not only for healthcare providers and patients with difficult-to-treat diseases, but also for the biotech sector. According to industry R&D data, increased success in early drug development through the use of artificial intelligence and machine learning could lead to an additional 50 new treatments within 10 years, which could also translate into a market of more than $50 billion. Enhanced by data analytics, this could present a significant opportunity as well as a breakthrough for the life sciences industry.
In recent years, technological advances in artificial intelligence have made it easier for humans to store and analyze large amounts of patient data. For example, rich genomic data, health records, medical imaging and other patient information can be mined and analyzed by AI to help develop new drugs more quickly and with a higher chance of success. Moreover, according to industry data, the cost of preclinical development can be reduced by about 20% to 40%.
Future Drug Development With AI
I think biotech companies can help more patients and generate new revenue in the future. For example, advanced data analysis capabilities and richer big data can help medical professionals assess patients' risks and detect diseases earlier.
On the other hand, for biotech companies, the median investment required to bring a new drug to market is probably close to $1 billion, and the true cost of R&D can be as high as $2.5 billion, taking into account the potential for abandoned trials and clinical failures along the way. So I think AI in this area may save companies unnecessary trouble and can provide tremendous value. However, investors may still have little confidence because of the high risks involved in creating viable new treatments. But some experts predict that there will be an inflection point in this area in the next two years, with increased collaboration between AI drug developers and large biopharmaceutical companies, and the sharing of data will make a difference, so I think that's one of the trends that we can probably watch in this area in the future.
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