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How AI is Transforming the Life Science and Pharmaceutical Industries

The pharma and life science industry has to deal with increasing regulatory, reducing the R&D productivity, impact of artificial intelligence in the (AI) value chain, and difficulties to growth and profitability. The pharma and life science industry is forced to transform their status quo due to the regulatory changes conducted by the far-reaching Patient Protection and Affordable Care Act (PPS) in the US.

Even though the healthcare system’s result is deteriorating and new epidemics are emerging, the industry is dealing with rising R & D expenses due to the increasing cost of regulatory compliance. Customer demographics are also changing because of the intense regulatory transformation. The growth in the life science and healthcare sector is boosted by developing APAC and Latin American regions.

Do Check — Life Sciences Review

Disruption in life sciences

The pharmaceutical companies can utilize AI in various methods to promote informed decision making on every part of the business. In the healthcare sector, making an informed decision during clinical trials, designing, planning, and manufacturing will improve collaboration in the systems, process efficiency, drive competitive advantages, information sharing, and cost optimizations.

Artificial intelligence helps the pharmaceutical industry make decisions based on engineering, real-time, data mining, and algorithms. They can respond to the following primary business value chain disruptions.

AI-driven drug discovery

With AI-based drug discovery, scientists can source their scientific findings and information from external labs or internal knowledge. It helps them start discovery as soon as possible and decrease the time of product development due to which it can be launched in the market faster.

Reduce cycle times for clinical trials

The pharmaceutical industry can also decrease cycle time because of the enhanced machine-based algorithm’s better information.

Supply chain transformation

The healthcare sector can also develop a predictive algorithm by combining internal and external data. It will help them decrease the unexpected deficiencies in the availability of drugs, impacting customer service levels, and even losing sales revenue.



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