The use of artificial intelligence (AI) in drug discovery and development has the potential to make a significant impact on the way new drugs are developed in the market. This blog will look at the challenges and benefits of using AI in drug development.
With digitalization and technology moving at an incredible pace, it would not be wrong to call the last decade, the golden era of pharma and healthcare companies. According to Artificial Intelligence (AI) report, the global market of Artificial Intelligence (AI) in the Drug Market will be worth around $2994.5 million by 2026 with Microsoft, Deep Genomics, IBM Corporation, Atomwise Inc, and many other well-known tech companies leading the movement.
In this article, we will be observing the advancements that artificial intelligence brings to drug development, explaining the key challenges organizations face while adopting AI tools, and going deep into the popular use cases of AI in pharmaceutical products.
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How AI can be Useful in Drug Development & Healthcare?
Artificial intelligence can help healthcare industry professionals by diagnosing patients after analyzing their symptoms and predicting the risks related to the treatment. It can also detect abnormal results. In the field of drug development, artificial intelligence is helping companies by using a wide range of data to evaluate and identify how different patients respond to drugs and also helps in developing new drugs much more cheaply and efficiently.
Benefits of AI
The impact of artificial intelligence cannot be comprehended in the pharmaceutical industry. Here are four key advantages of AI in drug development:
1. Constant Advancement
Along with helping humans with basic tasks, artificial intelligence also uses the latest technologies in computing and biology. This process is always evolving and advancing with increases in innovation and low costing AI tools. Artificial intelligence plays a vital role in drug development now and will do in the future.
2. Higher Predictivity
During drug screenings, the enhanced power of predictivity used by AI tools positively impacts the process of meaningful interactions. Hence, by going through a fastidious and rigorous approach to the parameters, we can remarkably reduce false positives.
We all know AI is an objective science, meaning, the AI-based drug development process does not factor in any sort of external interests like personal interests, prejudice, existing knowledge or anything else like humans do which can affect and hamper the development process.
4. Reduced Human Inefficiencies and Streamlined Process
With the help of artificial intelligence and virtual labs, human errors are bound to decrease over time. The machinery and advancement of AI also help in streamlining the process, thus reducing hours of human resources.
- Revolutionisation of Medicine: Accelerates Research & Clinical Trials
AI can also help to predict how drugs will interact with other drugs and with the human body, reducing the need for costly and time-consuming clinical trials. Ultimately, AI has the potential to revolutionize the drug development process, making medicine deliveries faster, cheaper, and more effective.
There are still several challenges that pharmaceutical organizations face while working with artificial intelligence despite the growing interest and potential in AI-based technologies:
1. Lack of Biological Data
Biological data plays a vital role in bioinformatics. They offer researchers and scientists an opportunity to access a wide range of biological data that includes genome sequencing of almost all kinds of organisms. Artificial intelligence depends on these data types to understand how a patient responds to his treatments.
The pharma sector is highly regulated, requiring full transparency and disclosure for each stage of drug development. This usually makes AI development lengthy and costly. Both regulators and companies should work together in making transformation initiatives to streamline the functioning of artificial intelligence.
3. Lack of Talent
Handling artificial intelligence is no joke, it requires highly skilled professionals who not only know the basics of AI but have a complete hold on the same. Recruiting such skilled professionals is not easy as individuals with such a high skill set are scarce in the market. Hiring such individuals can also incur additional costs.
4. Data Bias
The human population has a long history of being misrepresented in medical datasets. If the data is misrepresented for an entire community, there can be fatal outcomes. To reduce this risk, Machine Learning teams should focus on increasing transparency constantly and reducing bias from the artificial intelligence learning models.
Use Cases of AI
We must recognize the role of artificial intelligence in pharma drug development. By knowing the fields where AI can be applied throughout the medical industry, we can help further. Below mentioned are a few categories into which AI can be broken down:
- Drug Discovery
- Pharmaceutical Manufacturing
- Quality control and assurance
- Monitoring and Clinical Trial Design
- Pharmaceutical Product Development
- Pharmaceutical Product Management
We have discussed all benefits of AI in drug development, mentioned the key challenges, and discussed a few ways how it can be utilized. To sum things up, artificial intelligence is capable of doing things that humans could never do, it can make a significant contribution in the space of technology that can revolutionalize the whole drug discovery process. As many believe artificial intelligence is the breakthrough technology, it will soon become the standard practice in the coming years. A clear artificial intelligence strategy can expand the horizons of pharmaceutical companies and help them dominate this competitive market.
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