5 Ways by which Artificial Intelligence can Boost Pharmaceutical Industry?
Artificial Intelligence (AI) was first applied drug product development in 1990s, by using neural networks to predict the features of immediate release of the oral tablets. Later Artificial Intelligence enhances the process control by ensuring the consistent product quality and by predicting the quality deviations. AI in pharmaceutical industry also analyzes the real world data for detecting the adverse drug reactions and maintaining the safety of pharmaceutical products.
How Artificial Intelligence can Boost Pharmaceutical Industry
There are numerous ways in which AI can boost pharmaceutical industry by leveraging the pharmaceutical company marketing in the following ways:
1. Clinical Trial Optimization
Artificial Intelligence in pharma helps in identifying the suitable candidates by analyzing the health records and genetic data of the biomarkers and aids in the development of the targeted therapies and also improving the diagnostic accuracy accordingly. AI tracks the patient’s progress and for the best outcomes adjust the protocols in the real time.AI detects and addresses anomalies or protocol deviations promptly by reducing trial risk. With the predictive analytic AI identifies bottlenecks or dropouts risks by allowing proactive interventions.
2. Predicting Drug Efficacy
Artificial Intelligence plays a very crucial role in predicting drug efficacy with in the pharmaceutical industry. AI evaluates the genetic variations and patterns in the patient’s outcome. AI predicts efficacy based on the datasets of successful and failed drugs as well. Molecular docking simulations predicts that how a drug interacts with the target. After this AI identifies the biomarker who correlates with the positive responses to the particular drug. From the dynamic adjustments in the trial protocols AI monitors the clinical trials and then maximize efficacy.
3. Drug Discovery and Design
AI in the pharmaceutical industry analyzes the algorithms that can identify the potential drug candidates with the vast datasets of molecular and genetic information. With the pharmaceutical marketing strategy, AI predicts the efficacy and designs the new drug molecules with the desired properties and thus contributes in accelerating the speedy discovery phase by reducing the cost on Research and Development.
4. Supply Chain Management
The pharmaceutical marketing strategy uses artificial intelligence to forecast the inventory needs and then manages the stock levels accordingly. It also supports in improving the logistics for the on time delivery of the desired products and reduces its cost with the further delays, for this it improves production planning by preventing shortages or over production. AI also inspects manufacturing and distribution processes to ensure compliance with Good Manufacturing Practices. It also automates documentation for compliance with the local and international regulations.
5. Drug Repurposing
AI helps in identifying the new applications for the existing drugs by the identification of different patterns in the biological pathways. AI also evaluates the interaction of existing drug molecules with the different disease targets and predicts the drug binding with the different alternatives. Pharmaceutical company marketing focuses on powering the AI to construct complex biological network to identify the pathways between drug and disease. It identifies potential synergistic effects when repurposing drugs in combination therapies.
AI allows pharmaceutical companies to optimize the existing assets while addressing emerging healthcare challenges.
Key Considerations for Effective AI implementation in Pharmaceutical Industry
Since AI implementation has already proven successful even in the Pharmaceutical industry, but there are certain key considerations which need to lookout for the effective implementation of AI.
l Data standardization
Ensure that the datasets available for AI training must be accurate and comprehensive. Always use standardized data format to enable seamless interoperability between the systems.
l Regulatory Compliance
Align all the AI applications with the regulatory compliance from the authorities like FDA, EMA and so on. Adhere with the data protection law to safeguard the personal details and information of the patient.
l Technology and infrastructure
As per the pharmaceutical marketing strategy always utilize the cutting edge-technology like NLP, predictive analytic and deep learning. Always ensure that the AI solutions are compatible with existing pharmaceutical system. For the scalable infrastructure invest in the robust computing power and cloud platforms.
l Cost-effective Analysis
Always focus on the AI solutions that deliver long-term value in return. Ensure to assess the cost of implementing AI in comparison with the potential gains in efficiency and accuracy as well.
l Risk Management
Always ensure to test AI algorithms for the reliability and robustness. For the AI-driven decisions clearly define the accountability for the unintended outcomes. Required continuous monitoring of the AI system for detecting errors and update any new model with thaw necessary data if required.
Wrap-up
Pharmaceutical Industry can effectively leverage artificial intelligence for the better acceleration of innovation, enhanced drug safety, improving clinical trial success rates and so on by impacting every aspect from research and development to efficient patient care.