How AI Changed Pharmaceutical Industry and Drug Discovery

How the AI has changed the pharmaceutical industry and the drug discovery

Artificial Intelligenceis leveraging the global pharmaceutical industry. It has completely revolutionized the landscape of the medical industry. AI has made an unparalleled impact and taking the complete world of drug development to the next level.

In the pharmaceutical research and development field, there are limitless potential applications of AI. However, the improvement in the pharmaceutical industry has emerged as one of the most exciting and promising use cases of artificial intelligence in drug development.

Enabling predictive power in the R&D process

Artificial intelligence in drug development has made a compelling influence in the field of pharmacy, which is perhaps the most exciting and biggest change that it’s bringing to the pharmaceutical industry.

AI can effectively reduce the total number of clinical trials up to 70% by predicting how the drugs are going to interact with the patients. The analysis and insights offered by AI help remove some of the random elements which hinder clinical trials and reduces the need to compensate for some hindering factors.

Identifying clinical trial candidates

Identifying clinical trial candidates

AI helps to find patients to participate in the trials.

AI analyses genetic information to identify the appropriate count of patients for a trial and determine the optimal sample size.

Moreover, it can read the free-form text which patients enter into clinical trial applications and unstructured data like doctor’s notes and intake documents.

Drug Discovery and Manufacturing

AI has been proven successful in the field of drug discovery. It also helps in the initial screening of drug compounds based on biological factors.

To validate the hypothesis, the utilization of AI has proven to be an efficient way to examine enormous amounts of data. It is playing a significant role in drug target identification and validation based on target-based, phenotypic, drug repurposing, and distribution.

Precision medicine or next-generation sequencing helps in the faster recovery of drugs and personalized medicines for patients.

Especially when pharma companies need to implement drug trials, it reduces the time taken to test a drug and check its side effects in the market. It results in cost savings and lower-cost drugs available for patients. For instance, researchers are utilizing longitudinal electronic medical records to identify and validate novel cancer drug targets.

Digital Therapeutics/ Personalized Treatment

Artificial Intelligence can be utilized to identify individuals with certain physical disorders like gum conditions, and skin disorders to fetch early insights into the state.

Utilization of AI in the drug adherence

Artificial Intelligence can be used to evaluate remote monitoring and algorithms to evaluate the test results. In case, if patients are not following the trial rules, AI can be utilized to either remove the ones who don’t follow the trials.


Wearing eye-tracking glasses helps to capture and analyze using AI. This analysis includes Areas of Interest, time spent to first fixation and time spent, gaze plots, heat maps, and video replays. Hence it helps to understand customer behavior and product placement.

Predictive Biomarkers

Artificial Intelligence in drug discovery

Biomarkers play an important task in the context of medical diagnostics, especially in the process of drug discovery and development. Artificial Intelligence outlined the biomarker models which are trained using large datasets. Before the test is conducted in humans, it is used to identify potential responders to molecular targeted therapy.

How is AI used in Drug discovery?

Drug discovery is also a field that is also covered under the influence of Artificial Intelligence. During the Covid-19 pandemic situation, AI has been an efficient contributor to drug development and has reduced the initial step of handling suitable candidate molecules for testing. The shift towards its artificial intelligence turns out to be a catalyst behind the process of drug development.

Molecular Target Identification

This stage of drug development includes the identification of genes, proteins, or other molecules which can be used as a target to measure drug potency. Moreover, AI and machine learning utilize computer vision to understand 3D protein structures and molecules. It proves beneficial to analyze molecules and prioritize effective targets.

Drug Repurposing

In general, drugs interact with other molecules than the target molecule, hence it is suggested to identify the drug molecule interaction to repurpose drugs. Hence for this purpose, artificial intelligence is used to analyze the interaction between the drug and off-target molecules to establish any possible relation. Artificial Intelligence is also used to speed up the time required for drug development and its implementation in clinical practices.

Speed up the Clinical trials

How many times you have waited at the hospital to fetch your data? Yes, it is the most important task which requires analyzing and monitoring data. AI algorithms can process large amounts of data for quicker and more accurate results. As a result, you can yield better patient compliance and reduce the cost. Henceforth it reduces the impact of drugs and treatment with reliable evidence.

Artificial Intelligence is helping pharmaceutical companies improve clinical trials in the following ways:

1. Improving patient recruitment-  AI ensures to analyze patients from a broad pool and identify patients for a given trial.

2. Optimizing trial design- Pharmaceutical companies are exploring innovative methods to identify the inefficiencies in their clinical trial processes to speed up the process.

3. Output optimization- AI offers help to resolve challenges in clinical trial administration by proactively identifying the interaction of the patient depending upon the validity of the trial.

The Conclusion

The growing adoption of artificial intelligence for clinical trials is driving the demand and benefits of AI in drug discovery in the medical field. Earlier it required an average of 10-15 years to bring a new drug and now by utilizing AI models and analytics tools, the clinical trial phases can be accelerated in a hassle-free manner.

For instance, the adoption of AI tools like Pfizer has speedup up drug discovery and reduce the drug development cost in the drug development processes.

Global AI is expected to grow from $0.91 billion in 2020 to $1.27 billion in 2021 with an annual growth rate of 39%. With more and more companies adopting the latest AI technologies, this market is expected to reach the rate of $5.94 billion in 2025 at a CAGR OF 47%.

The availability of incredible open-source AI platforms has improved the efficiency of clinical trials and accelerated drug development.

It is expected that companies are expected to invest around $6.6 billion in AI and healthcare is one of the most significant areas of growth. AI helps with quality control, carrying out predictive maintenance, automation process, waste reduction, and design optimization. Therefore, many companies operating in the market are focusing on introducing the latest technologies to survive in AI in the pharmaceutical industry.

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