Blog | Reasons to use the Cloud and AI in Drug Discovery

Reasons to use the Cloud and AI in Drug Discovery

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Over the past few years, businesses are digitizing their operations on vast scale, and pharmaceutical sector is no exception to this. Digitization comes with its own set of challenges such as gathering massive data, analyzing it and using the analyzed data to decipher complicated data challenges. Artificial intelligence (AI) has the potential to overcome these challenges. Organizations are using AI technology to handle immense volumes of data with better automation, generate data driven insights, mimic human intelligence and much more.

The wide range of benefits offered by AL is increasing its adoption in almost every business. Today, many leading pharma companies are leveraging AI technology to enhance their processes of manufacturing, drug research and development. A news portal predicts that nearly 50% of global healthcare companies will be adopting AI technologies by 2025.

But why are pharma companies increasingly adopting AI? What is the role of AI in drug discovery?

Let’s get to know through this article. Read on to understand the role of AI in drug discovery, how AI is helping modernize the traditional drug research method and how the overall drug discovery process has become faster, better and cheaper with AI technology.

Applications of AI in Drug Discovery

Why are pharma companies using AI in drug discovery?

The traditional process of finding medicines is complex, lengthy, and expensive. The time taken for developing a new drug varies from 10-14 years with an investment of about 3-4 billion USD. This time and cost estimation covers all the phases from research to manufacturing of a drug. However, by using the true potentials of the various resources of AWS cloud, and the state-of-the-art artificial intelligence algorithms and techniques, we can significantly reduce the time and cost to an extent. Some of the AI aspects that contribute to quicken the drug discovery process are:

• Data analytics capabilities of AI in drug discovery let researchers to swiftly navigate through loads of data points that can help gauge the target molecules’ capabilities.
• AI in drug discovery is expediting the analysis of massive medical data sets, generate data-driven insights, and predict future needs.
• Predictive analytics capabilities of AI contribute to identify and develop accurate chemical compositions, speed up trials and decide which new drug to manufacture.
• AI is contributing to manufacture good quality medicinal products, filter and employ best-matched patients for clinical trials and enhance the protection and efficiency of drugs during clinical trials.

All these aspects are accelerating the whole process of drug research and development making new drugs available in market at less cost and in shorter time. That's why pharma companies are increasingly using AI in their drug discovery and development programs.

As per a recent survey the global artificial intelligence (AI) in drug discovery market is expected to grow at a compound annual growth rate (CAGR) of 31.6%. Some of the major reasons leading to the increased use of AI in drug discovery are detailed below.

Discovering a novel drug includes several batches of design, chemical combinations, testing, and clinical trials. Screening huge sets of molecules to identify the correct one having the potential to be a drug takes a lot of time. AI in drug discovery helps researchers to quickly navigate through billions of chemical and molecular compounds to find a potential target.

The drug discovery cycle includes various stages, and the initial stages of this cycle are the most time and resources consuming. AI can be used to make these stages more efficient and rapid and given below are some of the drug discovery stages which AI can expedite:

Target identification. This stage includes finding role of the best suited therapeutic target (gene/protein) in a disease. It follows a trial-and-error functional method.
Drug molecule design. An inventive process of designing a new medicine as per the knowledge of the identified target.
Chemical combination. A huge number of chemical compounds are quickly produced on a small scale in small reaction cells.
Drug screening. In this stage, potential medicines are identified and optimized before filtering candidates for clinical trials.
Clinical Trials. A research study performed in people to evaluate a medical intervention. This is a primary testing way to find out if a particular new drug is safe and effective in people.   

Pharma companies are using artificial intelligence to optimize the manufacturing of drugs. This is done by managing waste or supply chains with the help of AI-enabled predictive analysis. 

AI in drug discovery contributes to predicting the finest combinations of chemicals for a drug composition with its possible outcome. Using AI in drug discovery allows researchers try several different chemical compositions and explore their possibilities for being a drug.

The predictive analytics capabilities of AI in drug discovery help researchers filter the right patients to participate in clinical trials. Artificial intelligence selects the best candidate for the trial based on patient’s medical records, demographic information, or ethnicity. To generate valuable insights, AI also contributes by monitoring and collecting data about the drug's effects on a patient.

How is Cloud Computing Accelerating Drug Discovery?

Virtual screening plays a vital role in the process of drug discovery. But the practical application of virtual screening is expensive as it needs the use of computational servers, graphical systems, and costly modeling software platforms. This is where cloud computing can help to build a cost-effective solution. Cloud computing is budget-friendly, elastic, and fully managed by the provider. Therefore, it will be economical to use cloud as a substitute to these massive internal resources required for using virtual screening.

Today, many leading cloud providers in the market are offering healthcare exclusive services such as CentralReach, Amazon Comprehend medical, NextGen Healthcare HER, etc. AWS offers a whole range of services for medical data processing, analysis, and storage. These services help to extract and understand unstructured medical data. You can store, transform, or query the health data in minutes. With these features, researchers can quickly generate insights that can be further used in drug discovery and development. 

Pharma companies are using cloud-based services on a large scale to:

• Extract important health information from the unstructured medical text such as diagnoses, prescriptions, and reports.
• Determine relationships between extracted health information
• Relate the information to medical ontologies like ICD-10-CM, RxNorm, and SNOMED CT
• Automate and lower the cost of processing unstructured medical text
Analyse and make predictions with extracted medical data
• Create a chronological view of patient’s medical data and much more.

Overall, medicine companies are optimising the cloud to cut down cost and time needed for launching new drugs to the market. 


Artificial Intelligence is accelerating drug discovery and development by contributing to the faster processing of immense data, better drug design, impelling modernization, enhancing clinical trials, and supervising drug management. This will eventually reduce the new drug’s cost and time to market. Just like any other sector, healthcare and life sciences are also exploring the plethora of benefits that cloud computing offers.  

Leveraging the cloud and AI in drug discovery is helping to turn impracticality into reality. However, many organizations are still skeptical about using these technologies. Some of the major challenges in adopting artificial intelligence by pharmaceutical industry are a lack of substantial amounts of data or budget for small companies, lack of skilled staff that can operate cloud and AI-based platforms, etc. These challenges can be solved with the help of industry experts and service providers who can help you design the right AI or cloud strategy in line with your business goals that too within your budget. Looking at the value adds that AI is capable of, ignoring to adopt it will only delay the huge benefits that AI can bring to your business.  

Do you want to explore the immense possibilities that AI can bring to your business? Contact us today to learn more about how we can help your company.  

Book a 1-hour free consultation with pricing details.  


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