Artificial intelligence (AI) and blockchain are two of the most promising digital technologies that the world has seen so far. These have already brought drastic revolutions in multiple sectors and the world of pharmaceuticals is no different in this case. Let us see how.
Research for Innovation of New Drugs
Pharmaceutical manufacturing companies
from all round the world, are investing on ultra advanced machine-learning or ML algorithms, and AI based tools and techniques; in their ongoing research for innovation of new drugs.
These intelligent tools work on exponential amounts of data; which can further be used to solve challenges associated with complicated biological networks. The involvement of these AI-Blockchain based tools extend from studying the multiple patterns of various diseases to even recognizing the correct drug compositions that would be best suited for treating specific traits of a particular disease.
This eventually makes it easier for the pharmaceutical manufacturing companies to take their investment decisions accordingly; in their quest of discovering new drugs that would have the highest success rate against any disease or medical condition.
P-Value Standards and Clinical Trial Success
P-values are a standard measure for the effectiveness of new drugs in Phase II trials, where it is decided whether or not to push the drug to the Phase III.
The concept of p-values is such that if the p-value for any drug is below 0.05, that means there is less than 5% chance that the new drugs effectiveness on patients is due to a random chance. In other words, this means that there is 95% chance for the drug being actually effective. A drug that achieves a p-value of 0.05 or less in Phase II trials will typically be advanced to Phase III.
Unfortunately, in reality it is much more complicated and less predictable than statistical models might imply. Its not actually the case that 95% of Phase III drugs achieve success; in fact, the success rate of Phase III drugs can be as low as 30%. The higher-than-expected failure rates of late-stage trials are the result of many factors, including discrepancies between Phase II and Phase III testing populations and end-points.
In order to avoid such low success rates, researchers need to leverage new technologies like artificial intelligence and blockchain to enhance clinical trial design and execution.
This is when AI and blockchain technologies are incorporated to increase the success rates of late-stage clinical trials, saving both time and money, thereby getting more effective research results.
AI has shown great results in improvising the Research and Development (R&D) process concerning various pharmaceutical drugs. This contribution includes designing and identifying of new molecules, target-based drug validation and discoveries, and various other concerns on the similar line.
Sometime back, MIT published a report saying that hardly about 13.8% of drugs successfully pass the clinical trials, while any pharma company ends up paying around US$ 2 billion for a drug to complete the entire process of a single clinical trial and get the much required FDA approval. This is the exact reason behind why the pharma contract manufacturers in India
are moving towards AI, in order to improve the success rates of new drugs, create more affordable drugs and therapies, and most importantly, cut down the huge operational costs.
Privacy and Management of Medical Data used in R&D
R&D in the world of pharmaceuticals calls for collection, maintainance and analysis of a huge amount of data. As a matter of fact, mere collection and analysis of medical data is not sufficient. This requires strict regulations assuring its privacy or accessibility.
But unfortunately, Indian pharmaceutical sector has already seen multiple cases of data breaches, that has resulted in the disclosure of several healthcare records; which definitely have brought adversities. Again, managing the sensitive medical data via traditional approaches can be a complex task since this data is dispersed over different healthcare databases.
This is where blockchain comes as a hero by creating a secured and unified platform for storing and managing all relevant data in single location. For example, huge amount of medical data can be stored in form of blockchain blocks; identifiable via a unique code. This process authorizes the sharing of health information or blocks, required for various R&D processes, without revealing the unique code.
Higher Efficiency in R&D on the Various Steps of Drug Manufacturing
By now, AI has been implemented at various stages of pharma manufacturing; for higher productivity, improved efficiency, and faster production of life-saving drugs.
Involvement of AI has improved all the manufacturing aspects like quality control, waste reduction, design optimization, process automation, etc.
AI and Blockchan have replaced many of the time-consuming old technologies pertaining the R&D segment in Indian pharma, thereby enabling the pharma companies to launch drugs much faster, and at cheaper rates. These have not only increased the ROI by limiting the human intervention, but also curtailed chances of human error.