We are witnessing a completely transformed healthcare industry due to the impeccable progress within life sciences research and development. The credit for effective treatment of medical ailments goes to the clever use of artificial intelligence. By leveraging scientific literature, omics, and patient’s overall clinical data, the healthcare and pharmaceutical industry has made itself worthy of driving smarter decisions.
Artificial intelligence and the pharmaceutical industry
Artificial intelligence or AI is the technology that uses computers, along with tried and tested automated algorithms to carry out certain tasks, otherwise requiring human intelligence. Recently, AI is widely being used in the pharmaceutical industry for discovering new drugs, biochemical modeling, bioinformatics, drug research, predictive toxicology, etc. in addition to that, the advancements in Machine Learning and Deep Learning is further strengthening the role of AI in the pharmaceutical industry.
For better results, the pharma industry is utilizing AI where it is best suited; i.e, in repetitive tasks lacking efficiency. The majority of pharmaceutical industries are investing in AI because it’s harmless and it helps in cutting back prices. The artificial intelligence in the pharmaceutical industry comprises three major divisions - Discovery, Development, and Commercialization.
Discovery: Due to the lower risk and no direct impact on patients, pharma industries prefer the use of AI in drug discovery. A range of parameters; as if, genomics, as well as molecular and cellular structure databases, empowers machine learning to perform efficient analysis.
Development: By effectively screening, identifying, and enhancing the engagement of patients, AI is helping find proper patients necessary for clinical trials. By combining human wisdom with experience and intuition, AI is playing a dominant role in drug development.
Commercialization: The advanced AI brings about precision/predictive medicine, diagnosis, quality assurance in cross-company, client service bots, drug personalization, and an array of radiology applications. AI helps in structuring a large volume of knowledge needed to sell.
AI Applications in pharma
Although the use of AI applications in pharma is obvious, its adoption is slow. Due to increased awareness and AI looked after as the next big thing, pharma companies adopting and adapting to the AI applications can enjoy a competitive edge. Here are the top five AI applications widely used in the pharmaceutical industry.
To improve the manufacturing process:
To improve the manufacturing process:
Pharmaceutical companies are using AI applications to reduce wastage and improve output resulting in an efficient production process. Additionally, AI is also programmed to perform quality control, lessen design time, enhance production reuse, carry out predictive maintenance, and much more.
To design and discover drugs:
To design and discover drugs:
With AI, the time required from drug discovery to market is reduced drastically; especially, the larger time gap during drug trials and getting it approved. AI plays a pivotal role in lowering drug costs and making more treatment choices available. It acts by drug target identification and validation; target-based phenotypic as well as multi-target drug discoveries along with drug repurposing and biomarker identification.
To process biomedical and clinical data:
To process biomedical and clinical data:
To read, group, analyze, and interpret large volumes of textual data is the most developed and widely used AI algorithm. AI collects, scans, stores, and interprets an enormous amount of growing data ranging from handwritten notes to test results and from patient logs to imaging scans. It helps in speedier research, effective cross-referencing, combining, extracting, and presenting data in a usable and understandable format.
To find rare diseases and deliver personalized medicines:
To find rare diseases and deliver personalized medicines:
Based on genetics, patient data, scans, tests, images, and patients’ biology, AI is programmed to detect rare diseases like cancer or predict serious health conditions like a heart attack. Moreover, AI in pharma is programmed to deliver a personalized treatment plan based on patient's clinical and historical data which includes, drug allergies and reactions.
To identify precise patients for a clinical trial:
To identify precise patients for a clinical trial:
The AI applications developed to find a perfectly suitable patient for a clinical trial is empowered with advanced predictive analytics. By analyzing the patient information, his/her clinical data, and genetic information, the AI can identify the right patient for a clinical trial. To make a selection, the AI gathers, reads, and interprets the free-form text entered by a patient in a clinical trial application and some unstructured data from doctor’s notes and other clinical documents.
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