Predictive Analysis in Pharmaceutical Industries

Predictive Analysis in Pharmaceutical Industries

Predictive analytics is an approach used for forecasting based on previous data and other critical indicators. It relies on information collected and past events to determine the best possible approach for business growth. Pharmaceutical companies always rely on empirical data i.e. data collected by experimenting. This empirical data with predictive analytics can provide information regarding :

=> Identifying Patterns
=> Testing theories
=> Measuring efficacy of treatments
=> Observe hidden insights
=> Optimise drug discovery

Challenges for the manufacturers

a. Growing competition for generic pharmaceuticals

Upcoming patent cliffs are advantageous for small manufacturing companies but create heavy competition with the pharmaceutical giants. As a result of this competition, several major companies have lost their market exclusivity in the past years.

b. Pharmaceutical Fraud

Pharmaceutical fraud remains a critical challenge for the industry. Problems like off-label marketing, drug switching and unlawful kickbacks are just some of the mishandles which are necessary to be addressed soon.

c. Cybersecurity threats and data breaches

Increasing value of consumer data makes it more vulnerable to data breaches and cyber attacks. Pharmaceutical industries are the fourth most impacted industries from such attacks. On the manufacturing side, use of IoT based devices in manufacturing process also makes it vulnerable to attacks

d. Supply chain disruptions

In the recent global pandemic, many supply chain logistics couldn’t withstand the situational crisis. Long manufacturing times and unpredictable demand led to drug shortages. Lack of visibility and transparency further aggravates this situation.

e. Lack of transparency

This is the most common supply chain issue, it is always extremely difficult to trace a problem to its source because of lack of transparency. At times drug imitation, unreasonable price rise and unsuitable drug consumption happen which are almost impossible to trace back to the origin of the cause.

Applications of Analytics in Pharma

a. Medicaments Stockout Prevention

Based on the inventory and the products sold in a given time frame, systems are able to determine the products which will require replenishment. This helps in better inventory management and one can even automate the process of ordering new medications required for restocking.

b. Personalised medicine

Medical professionals have developed systems which use lab tests, previous health records and genomic data to revise individualised treatment strategies. Smart algorithms can effectively sift through unstructured genomic data and also help in discovery of precision medicine.

c. Drug Discovery

Drug discovery is another eminent field for predictive analytics. It focuses on finding new compounds with specific chemical properties. It is a very resource intensive and time consuming process and will take quite some time for commercialisation.

d. Clinical Trial

Utilizing predictive analysis consulting, Pharma companies can improve success rates of certain clinical studies. Adverse and critical conditions can be analysed using EHRs and claims data to evaluate the success rate beforehand.

Advantages of Pharmaceuticals and Predictive Analytics

=> Enhance drug discovery and development
=> Identifying clinical trial candidates
=> Optimise Operational costs
=> Predicting treatment results
=> Drug discovery and design