Role of Artificial Intelligence in Pharmaceutical Industry

The global AI in the pharma market expanded to a size of nearly $699.3 million in 2020. The market is anticipated to increase at a rate of 32.9 %, from $699.3 million in 2020 to $ 2,895.5 million in 2025. Researchers claim that the application of these technologies enhances decision-making, maximizes creativity, increases the effectiveness of research and clinical trials, and produces new tools that benefit doctors, patients and regulators.Computer-aided drug designs have recently supplanted more traditional methods of medication development. A lot of AI is being applied to advance drug design methods and dosage requirements. Additionally, AI makes it simple to identify the target proteins, increasing the likelihood that the proposed medicine will be effective. Each phase of the medication design process uses AI technology, which lowers the health risks associated with preclinical studies and also significantly lowers the cost.

The AI in pharma market was dominated by North America, which accounted for 43.2% of the total in 2020. Western Europe, Asia-Pacific, and then the other regions were placed after it. The AI in pharma market would have the fastest growth in the future in South America and Asia Pacific, with CAGRs of 42.7 % and 38.6 %, respectively, during the years 2020 to 2025. These will be followed by markets in Africa and Western Europe, who’s CAGRs are anticipated to be 35.77 and 34.72 %, respectively, from 2020 to 2025.

 AI can support rational drug design, aid in decision-making, identify the best course of treatment for a patient, including personalised medications, manage the clinical data generated, and use it for future drug development, it is reasonable to assume that AI will play a role in the development of pharmaceutical products from the bench to the bedside.

A drug's discovery and development can take over ten years and cost an average of US$2.8 billion. Even then, nine out of ten medicinal compounds fall short of passing regulatory approval and Phase II clinical trials.In order to provide a platform for the development of treatments for conditions including immuno-oncology and cardiovascular illnesses, a number of biopharmaceutical companies, including Bayer, Roche, and Pfizer, have partnered with IT firms.

Numerous AI platforms for individualised patient care have received FDA approval throughout the years. While some of the systems detected brain bleeding on a CT scan or picked up irregular heart rhythms on an Apple Watch, others were utilised for remote patient monitoring.

The pharmaceutical industry's recent uptick in using AI capabilities does not appear to be slowing down. By 2025, over half of all healthcare organisations worldwide intend to develop AI strategies and widely use the technology. Based on the vast amount of pharmaceutical data and machine learning process, AI is a useful tool for data mining. De novo drug design, activity scoring, virtual screening, and in silico evaluation of a drug's characteristics have all been applied to artificial intelligence.

AI is mainly used in pharmaceutical industries forDrug discovery, Clinical Research, Disease diagnosis, Novel medication, Prediction and Data analysis.

Identification and diagnosis of diseases

AI is an innovative tool for diagnostic purposes. An innovative US biopharma company called Berg, for instance, is utilising AI to study and create treatments and diagnostics in the areas of oncology, endocrinology, and neurology. Their specialised AI-based Interrogative Biology® platform uses patient biology and AI-based analytics to distinguish between healthy and disease environments.

Radiation Therapy

It has been predicted that AI would play a significant role in this field in the future. Google's DeepMind Health is currently developing machine learning algorithms to distinguish between malignant and healthy tissues. The objective is to increase radiation planning accuracy while reducing harm to healthy organs that are at risk.

Identification of rare diseases and personalised medicine

Body scans can identify potential health problems based on a person's genetic makeup and use AI to detect cancer and other diseases early. IBM Watson for Oncology is now the market leader in AI for individualised treatment selection in the field of oncology, although being far from flawless. In order to make the best treatment decisions possible, it makes use of the medical data and history of each patient. A patient who was initially believed to have acute myeloid leukaemia recently had a rare kind of leukaemia, which Watson accurately identified. It purportedly looked at millions of oncology research papers in just ten minutes, correctly identified the patient, and then suggested an individualised treatment strategy.

Advantages of AI are as follows

1. Error minimization: AI helps reduce errors and boost accuracy with greater precision. Intelligent robots are used to explore space because they have durable metal bodies and can withstand the hostile atmosphere.
2. Difficult exploration: The mining industry demonstrates the value of AI. The industry of fuel exploration also makes use of it. By overcoming the mistakes made by humans, AI systems can study the ocean.
3. Daily use: AI is quite helpful for our everyday actions and tasks. For instance, GPS is frequently utilised during long journeys. Androids with AI installed can anticipate what users will input. Additionally, it aids with spelling correction.
4. Applications in medicine: Generally, doctors can evaluate patients' conditions and examine the negative effects and other health concerns linked to a prescription with the use of an AI computer. Applying AI programmes like various artificial surgery simulators can help trainee surgeons learn new skills.
5. Accelerate technical progress: The world's most cutting-edge innovations frequently incorporate AI technology. It tries to create novel compounds and can produce a variety of computational modelling software. Additionally, the creation of drug delivery formulations makes use of AI technology.
6. Unlimited capabilities: Machines are not constrained by any limitations. Machines without emotions are more productive and efficient than people in every way.

Limitation of AI are as follow:

1.    Expensive: The introduction of AI leads to significant financial outlays. The machine's intricate design, servicing, and repair are all very cost-effective. The R&D section needs a lot of time to build just one AI machine. The software needs to be updated frequently by AI machines. Reinstallations and machine recovery take a long time and cost a lot of money.
2.    No improvement with experience: Experience can help human resources. On the other hand, AI-powered robots cannot benefit from the experience. They are unable to distinguish between those who work hard and those who don't.
3.    Lack of originality: AI-powered machines lack both emotional intelligence and sensitivity. People are able to hear, see, feel, and think. They can think and be creative at the same time. Machines cannot be used to achieve these features.
4.    Unemployment: The widespread use of AI technology across all industries could result in significant job losses. Unwanted unemployment may cause human workers to lose their work habits and creativity.

Pharmaceutical Industry Can Adopt AI

Innovative treatment approaches are required to improve R&D outcomes, automate the healthcare process, and develop novel medications. That is achievable due to artificial intelligence.

•    Work together with businesses that specialise in AI-driven drug discovery to get the greatest advantages from professional advice, cutting-edge equipment, and experience.
•    Develop the skills of the internal team and provide your employees with the tools they need.
•    Select for open research initiatives to use AI for finding new pharmaceuticals. Partner with academics to embrace AI and help the pharmaceutical business flourish.

Recent AI Adoption

Novartis: AI isusedto predict untested components, hence researchers explore to find new cures.
Bayer and Merks & Co: Used AI algorithm to identify Pulmonary Hypertension
Mission therapeutics: Used AI to develop a formulation for Alzheimer’s
AstraZeneca and Alibaba: build AI to help patients with automated cancer diagnostics.
Apple: Used AI to screen children for autism.

Future of AI in the Pharmaceutical Sector

The use of artificial intelligence in the pharmaceutical sector is significant, and in the next years, there is simply no indication that this cutting-edge technology's uptake will slow down. AI and machine learning have the potential to revolutionise the healthcare sector, from automating administrative tasks to assisting in drug discovery. In order to improve R&D strategies and patient care, more businesses should start implementing this technology.

Conclusion:

AI is doubtless the next biggest step for the Pharma industry. Companies that are more flexible and adopt AI Faster will likely gain a strategic advantage.Pharmaceutical companies are turning to AI to reduce the financial costs and failure risks. The pharmaceutical and medical industries are likely to undergo a revolution thanks to AI, according to the projected growth of 40% from 2017 to 2024. Numerous pharmaceutical firms have invested in AI and are continuing to do so. They have also worked with AI firms to develop crucial healthcare tools.

References:

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6.    https://roboticsbiz.com/ai-in-drug-discovery-advantages-and-disadvantages
7.    https://mobisoftinfotech.com/resources/blog/artificial-intelligence-in-the-pharmaceutical-industry