The prices of the medicines are sky high. The reason is drug development costs are increasing, as critical modern needs include vaccines, chemotherapy, and novel antibiotics. But the disruptive technologies like AI, blockchain and big data can reduce the price to the affordable stage. The challenges are hereunder:
As per 2011 estimates, the total timeframe required for drug approval averages 14years. Most of the time is dedicated in R&D: discovery Takes about four-and-a-half years, a year in preclinical testing, one-and-a-half to two-and-a-half years in the three phases of clinical development and one-and-a-half months in submission to launch the medicine. The main issue is to identify the promising disease targets. AI or artificial intelligence software is helping with the automatically structuring big data. It helps the pharmaceutical companies to monitor public health data and to develop novel insights on potential targets of disease.
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Nature reported that for target validation 20 to 25 percent of published preclinical targets were replicable in in-house pharmaceutical experiments. AI can help in cross-referencing the scientific literature published with the sources available alternatively and which are less susceptible to bias. However, blockchain can further reduce the bias in clinical trials.
The complexity of Clinical Trials for Chronic Diseases
Chronic Diseases takes years to develop due to its complex non-linear predictive model. AI is one of the best hopes for managing the chronic disease because big data can be structured from daily life outside the clinic where most chronic diseases occur.
Lower Success Rates of small Development Groups
The large pharmaceutical companies outsource the first drug discovery phase to small organizations and become more agile and innovative. But the success rate is low for small development groups on approved molecular entities compared to the large organizations because they suffer from the lack of historical knowledge. As per NBC News, 16 pharmaceutical companies and 60 startups are using AI in 2018 for drug discovery, and I love this review.