Artificial Intelligence in Drug Discovery with Machine Learning

In this article, we discussed Machine Learning and Artificial Intelligence in pharmacy. Since this is a very broad subject, we decided to draw attention to one of its most important parts: Artificial Intelligence in the pharmaceutical industry’s drug discovery. But this time, we will take a slightly different approach.

In general, drug discovery is a very time-consuming and costly process. It is estimated that to put on sale just one new drug, you have to invest at least 350 million USD [6], and it takes around 10 years to do so.

Machine learning in drug discovery may shorten and cheapen this process. That is why artificial intelligence is getting more and more attention in the pharmaceutical industry. A growing number of pharmaceutical companies are considering or already using AI-based solutions in their research, development, and production processes. Let’s focus on the current AI solutions in the pharmaceutical industry.

Read more: Machine Learning. What it is and why it is essential to business?

Artificial intelligence in the pharmaceutical industry

Pharmaceutical companies are constantly looking for ways to shorten and cheapen this process. At stake are big numbers and human health. We do not need to say how many benefits it would bring if the drug discovery process were shorter and cheaper.

On the other hand, the sad reality is that many rare diseases are still waiting for a cure to be invented because, in many cases, it is not profitable for pharmaceutical companies to look for them. So, patients are waiting. If it were not for this issue, the lives of millions of people might be totally different.

But for that to happen, we need faster and cheaper solutions. And they are available! They are almost at hand! Machine learning and Artificial Intelligence in drug discovery.

Let’s see how ML and AI can change the pharmaceutical industry!

Read more: Machine learning in Healthcare

AI and ML in the pharma industry – forecasts

Developing a drug using artificial intelligence and machine learning can change the way we think about drug development. Before we turn to AI applications in the pharma industry, let’s check the forecasts for the future. As we can read in the Bekryl Intelligence report, “Artificial intelligence has the potential to offer over US$70 billion savings for the drug discovery process by 2028.

Additionally, the potential to boost a company’s ROI along with its time-saving process has led big pharmaceutical and biotech companies to invest heavily in technologies.” [7]

So the direction is clear – we have to invest in Artificial Intelligence in the pharmaceutical industry and machine learning in drug discovery if we want to see more new drugs on the market.

AI applications in the pharma industry

AL and ML are essential in the pharmaceutical industry. The application of AI in pharma is not limited to research and development. Today, AI is used at various stages of development, from identifying patient needs to regulating dose and analyzing treatment results. So, the key applications of AI in the pharmaceutical industry are listed here:

Drug Discovery and Manufacturing

The drug discovery and development of new medications is the main focus of artificial intelligence in the pharmaceutical industry. So, the most impressive AI achievements in the pharma are in the following areas:

• Data-based target discovery (for example, cancer drug targets)
• Next-generation sequencing
• Pre-clinical research and early-stage drug discovery
• Small molecule therapeutics
• New drug design
• New biological targets

Moreover, AI allows the optimization of manufacturing processes in pharmaceutical companies – the improvements can cover several areas, such as:

• improved waste management,
• supply chain management
• predictive maintenance.

Drug Dosage

Up to 60% of patients do not follow medical recommendations, which reduces the chance of success and increases the cost of treatment. [1] Artificial intelligence in the pharmaceutical industry is gaining popularity in monitoring regime compliance. Moreover, this can be done using various Internet of Things devices and centralized data collection.

A novel solution is ingestible sensors with RFID tags. These sensors provide a unique signal to a relay device, which then sends the signal to a cloud server as soon as the tablet is swallowed.

Digital Therapy and Personalized Treatment

Discovery AI can also develop personalized medicines based on the results of individual tests, genetics, allergies, and data on the patient’s reactions to previous treatment. Additionally, AI in the pharmaceutical industry is being used to discover primary treatment options with over-the-counter medications.

Clinical trials

Using advanced predictive analytics, AI helps researchers determine the appropriate group of patients for clinical trials. Furthermore, by analyzing the medical history, demographic data, and ethnicity, the AI determines the most suitable candidate for the trial.

Use Cases of AI Technology in the Pharmaceutical Industry

AI platform for optimization of drug dosage at an individual level

A group of researchers led by the National University of Singapore (NUS) used the artificial intelligence platform in the pharmaceutical industry, CURATE.AI, for the successful treatment of a patient with advanced cancer and complete cessation of the progression of the disease. THE VICAR.AI was used by the research team to continuously determine the optimal doses of each drug to ensure a sustained response. [3]

Image recognition for improving drug adherence

AiTure, a New York-based mobile SaaS platform, has developed an image recognition algorithm that helps track treatment adherence by recording video how a patient takes a pill. As a result, the face recognition technology then confirms that the right person has taken the right pill. [3]

AI for developing drugs for glaucoma

Santen, an ophthalmology company, has entered into a partnership with twoXAR, an artificial intelligence-based company, with the aim of developing new candidate drugs for glaucoma. twoXAR also uses a computing platform that allows the prioritization of new drug candidates that can be applied in ocular indications.[3]

AI helps companies find treatments for rare disease

The artificial intelligence platform HealNet enables scientists to improve drug manufacturing while decreasing time, costs, and risks. The company uses artificial intelligence technology to research existing medicines and repurpose them for the treatment of rare diseases. [3]

AI platform for drug design using chemical principles

PostEra is a San Francisco-based startup that specializes in medical chemistry and machine learning. Company is now working with Pfizer (PFE) on the development of machine learning for drug discovery. Moreover, the PostEra platform is based on chemical synthesis design methods and rules used by medical chemists and organic chemists for the synthesis of potential drugs. [4] It’s a successful example of how AI and ML in the pharma industry have great influence on the future.

AI-leading startups in pharmaceutical industry

Today, the number of companies using AI for the discovery and development of new drugs is growing every day. Here you can find leading AI startups in the pharma industry.

• Standigm – a South Korean AI startup in pharmaceutical industry that offers innovative solutions in the field of drug design. Standigm explores the hidden chemical space produced by artificial intelligence to create new molecules with the necessary characteristics.
• CytoReason – the Israeli startup analyzes multidimensional clinical data about people to provide data-driven target discovery. The startup’s platform uses machine learning algorithms and continuous statistical learning to identify disease-related cell / gene maps.
• Genome Biologics – another example is a German startup that develops preclinical drug discovery solutions. Pattern recognition and machine learning are used by the startup to compare databases of chemicals and drug discovery and repositioning processes with profiles of genes associated with the disease. In addition, it allows a company to discover new molecules and reuse existing ones for the treatment of cardiovascular diseases and cancer.
• DeepCure is a US-based startup that uses deep learning to find small-molecular medicinal compounds. This company integrates AI pharma algorithms, cloud computing, and MolDBTM, its own database with over a trillion different molecules. [5]

The future potential of artificial intelligence in pharmaceutical industry

Pharmaceutical AI truly has become a crucial component of drug discovery. The whole process of drug discovery AI is simply much cheaper. So, that leads to very optimistic forecasts – cheaper drug discovery means more drugs on the market. Which is heartwarming for the patients with rare and difficult to cure diseases, for which current pharmaceutical offer is simply insufficient.

Who knows, maybe in the not too distant future, drug development will take just a year instead of the current 10 years? Therefore, this is the real possibility, thanks to machine learning in drug discovery and artificial intelligence in the pharmaceutical industry.

To sum up

All in all, machine learning and Artificial Intelligence algorithms in drug development can be beneficial in many ways. Starting from designing the desired chemical compounds, that are a basis for future drugs, through analyzing huge amounts of data in order to minimize unwanted side effects up to the gathering proper candidates for the clinical tests. Futhermore, artificial Intelligence in drug discovery is a great milestone that assists human scientists in every single step of the long and winding journey to the discovery of new medicine.

So, do you run a pharmaceutical company? Are you interested in the implementation of Artificial Intelligence in your company? Just give us a call! We are always vitally interested in the cooperation with companies wanting to start a new phase of their development – with machine learning and Artificial Intelligence.

Also check out our machine learning consulting services to learn more.

Artificial Intelligence in Drug Discovery with Machine Learning – FAQ

What is the impact of AI and Machine Learning on drug discovery in the pharmaceutical industry?

AI and Machine Learning significantly impact drug discovery by making the process faster and cheaper. These technologies help identify potential drug targets, optimize manufacturing processes, and improve patient outcomes. This leads to more efficient development of new medications, potentially saving billions of dollars and reducing the time required to bring a drug to market from 10 years to a much shorter period.

Why is drug discovery traditionally a time-consuming and costly process?

Traditionally, drug discovery is time-consuming and costly because it involves extensive research, development, and testing phases. On average, it takes around 10 years and at least $350 million to develop a new drug. The process requires substantial investment in laboratory research, clinical trials, and regulatory approval.

How can Machine Learning and AI reduce the costs and time associated with drug discovery?

Machine Learning and AI can reduce costs and time in drug discovery by:

• Automating data analysis to identify potential drug candidates more quickly.
• Predicting the efficacy and safety of compounds using advanced algorithms.
• Enhancing precision in clinical trials by selecting suitable candidates.
• Streamlining manufacturing processes to improve efficiency and reduce waste.

This article is an updated version of the publication from Jun 29, 2021.

References

1. Nexcode.com. AI in Pharma. URL: https://nexocode.com/blog/posts/ai-in-pharma/#pharmacovigilance. Accessed June 29, 2021.
2. Forbes.com. The increasing use of AI in the pharmaceutical industry. URL:https://www.forbes.com/sites/cognitiveworld/2020/12/26/the-increasing-use-of-ai-in-the-pharmaceutical-industry/?sh=2676f5004c01. Accessed June 29, 2021.
3. Digitalauthority.me. Artificial Intelligence & Pharma: What’s Next?. URL:https://www.digitalauthority.me/resources/artificial-intelligence-pharma/. Accessed June 29, 2021.
4. Nanalyze.com. 7 Companies Using AI for Drug Discovery. URL:
   https://www.nanalyze.com/2021/04/companies-ai-drug-discovery/. Accessed June 29, 2021.
5. Startus-insight.com. 5 top artificial intelligence startups impacting drug discovery. URL: https://www.startus-insights.com/innovators-guide/5-top-artificial-intelligence-startups-impacting-drug-discovery/. Accessed June 29, 2021.
6. Forbes.com. The Cost Of Creating A New Drug Now $5 Billion, Pushing Big Pharma To Change. URL: https://www.forbes.com/sites/matthewherper/2013/08/11/how-the-staggering-cost-of-inventing-new-drugs-is-shaping-the-future-of-medicine/#36b42fd313c3. Accessed June 29, 2021.
7. Bekryl.com. Global Artificial Intelligence in Drug Discovery Market Size Analysis, 2018-2028. URL: https://bekryl.com/industry-trends/ai-artificial-intelligence-in-drug-discovery-market-size-analysis. Accessed June 29, 2021.