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Artificial Intelligence in Drug Discovery with Machine Learning (update: June 2021)

In this article, we talked about Machine Learning and Artificial Intelligence in pharmacy. It is a very wide subject, so we decided to draw more attention to one of the most important parts of it – Artificial Intelligence in pharmaceutical industry in drug discovery. But this time we will go a bit different way.
In general, drug discovery is a very time-consuming and costly process. It is estimated that putting 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 in pharmaceutical industry gets more and more attention. 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.

Artificial intelligence in pharmaceutical industry

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

From other side, the sad reality is this – currently many rare diseases are still waiting for the cure to be invented because in many cases it is not profitable for the pharmaceutical companies to look for them. So patients are waiting. If it would not be the 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! Almost at hand! Machine learning and Artificial Intelligence in drug discovery. Let’s see how ML and AI can change the pharmaceutical industry!

You may find it interesting – Machine learning in Healthcare

AI and ML in the pharma industry – forecasts

Developing a drug with the usage of artificial intelligence and machine learning can change the way we think about developing a drug. 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 saving 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 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 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 optimisation of manufacturing processes in pharmaceutical companies – the improvements can cover several areas, such as: improved waste management, supply chain management or predictive maintenance.

Drug Dosage

It is believed that 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 in a variety of methods, including the use of various Internet of Things devices and centralized data collecting.


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

Digital Therapy and Personalized Treatment

Discovery AI is also able to 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 pharma 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 the 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 Pharmaceutical Industry

AI platform for optimization drug dosage at an individual level

A group of researchers led by the National University of Singapore (NUS) used the artificial intelligence platform in 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 uses also a computing platform that allows to prioritize 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.

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.

The post Artificial Intelligence in Drug Discovery with Machine Learning (update: June 2021) appeared first on Addepto.



This post first appeared on Machine Learning, AI And Data Science Consulting, please read the originial post: here

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Artificial Intelligence in Drug Discovery with Machine Learning (update: June 2021)

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