Top 5 AI Use Cases in Pharma & Bio medicine
Top AI Use Cases In Pharma and Bio medicine
The use cases of Artificial Intelligence (AI) in the healthcare sector, especially in the pharma and biomedicine field, are gaining momentum.
Herein, we would like to go beyond the AI trends that exist in this ever-growing healthcare sector. Let’s start!
In our research, we found that approximately 50% of global healthcare companies will implement AI strategies and broadly adopt the technology by 2025. In particular, global pharma, drug development, and biomedicine companies will invest more in discovering new drugs for chronic and oncology diseases.
Biomedicine companies are adopting AI and its tools for conducting accurate laboratory and scientific tests and predicting the right diagnosis and treatment of disease. By automatically deriving patterns into various oncology diseases, AI use cases in pharma and biomedicine ensure wide opportunities and make workflows faster and more efficient.
In this article, we aimed at clearing the doubts that most healthcare business leaders have in mind such as-
- What are the major AI and Machine Learning (ML) applications that are increasingly used at the top pharma companies?
- Are these companies follow common AI trends to reap the benefits? If so, what are the AI trends for Pharma companies?
- How much global pharmaceutical and drug development companies are investing in machine learning and AI applications?
Now, we will directly move into our topic “how top pharma companies (like Johnson & Johnson, Roche, Pfizer, Bayer, and Novartis, etc.) are implementing AI applications.
I hope this article would help pharma companies to know how AI help them in generating increased RoI.
#1 Johnson & Johnson- The America’s top pharmaceutical company
Johnson & Johnson (J&J) has started implementing AI since 2015 after the collaboration with IBM’s Watson Health. IBM Watson is an AI-powered cloud system designed to process enormous amounts of healthcare data. It provides proof-based responses to professionals in natural language.
At present, the company is striving to put its total efforts to combine expertise and the power of AI and ML to come up with new drugs, treatments, and surgical methods.
It is a novel application of artificial intelligence in pharma and biomedicine. It is a trending role of AI in the pharma and medical field.
J&J has created a joint venture- Verb Surgical, in partnership with Google Verily in 2015 to develop AI and ML-powered surgical robots to perform minimally invasive medical surgeries. Still, research works ongoing on Verb’s robots and is expected to come into the market by the end of 2020.
AI In Drug Discovery & Development
Artificial intelligence in drug discovery is another significant Pharma use cases. The benefits of AI in pharma and biomedicine are not limited to robotic surgery and pattern recognition, drug discovery, design, and development are a few key roles of AI in pharma and biomedicine.
To remain competitive in this digital world, J&J continuing to merge its expertise and intelligent AI strategies to bring outstanding drugs and surgical solutions into the market.
The company is investing heavily in developing precision medicine. Using the capabilities of AI and machine learning technologies, the company is aiming to provide more personalized healthcare services to patients based on their genetic profiles. Hence, this will help to improve patient outcomes and reduce healthcare costs.
AI For Clinical Development
It is the best RPA use cases in pharma. RPA-Robotic Process Automation is one of the key technologies of AI and is being used to ensure accuracy in drug development and make clinical development activities faster. The real world use case of RPA in pharma is maintaining quality data, performing rule-based tasks, streamlining processes, and generating compliance-safety medical and clinical reports.
Get more information of RPA use cases in pharma and development cost of RPA software applications for healthcare!
AI to treat Alzheimer’s
AI for treating Alzheimer’s disease is the best application of artificial intelligence in pharma and biomedicine. We can say that it is the best AI use cases in pharma. In collaboration with WinterLight Labs, J&J reaps the benefits of an AI platform to monitor neuropsychological details to treat Alzheimer’s.
WinterLight’s speech-based smart AI platform can detect, understand, and record hundreds of measurable variables from a patient’s natural language. So that the automatic analysis of Alzheimer’s can be detected.
Future Plans Of J&J Using AI, IoT & Cloud Technologies
In addition to these, J&J continues to invest in existing digital initiatives to grab digital opportunities. For instance: J&J uses IoT to monitor product distribution, and their interaction with patients seamlessly.
By integrating IoT sensors into medical devices such as lenses and artificial joint replacement products, J&J was in plans to advance the clinical monitoring process of patients after surgeries.
If you’re ready to find a challenging business with AI, We’d love to meet you. CONTACT US to know more about the use cases of AI that help Pharma companies.
These are top pharma use cases on which J&J is spending more investments to remain competitive. Every application of artificial intelligence in pharma and biomedicine will offer the best results to organizations. Implementation of all the above-listed top AI use cases in pharma and biomedicine will streamline operations, increase the level of automation, and make processes smoother, faster, and more efficient.
AI Automates Admin Tasks
One of the key roles of AI in pharma and biomedicine is to automate the regular tasks of admin. Starting from records maintenance and recording novel drug data to clinical trials data and FDA approval copies, everything can be stored automatically using AI apps without errors.
#2 Roche Holding AG- Top AI Investor
Roche Holding AG is one of the global largest pharmaceutical and diagnostic companies. For the past few years, it is spreading announcements regarding how it is using AI technology to enhance its drug development operations rapidly.
Recently, in 2018, it acquired Flatiron Health. Flatiron Health is engaged in maintaining a vast amount of oncology data. This collaboration helped Roche to feed its ML systems for efficiently analyzing oncology disorders with more accuracy.
Later, in 2019, the company together with its subsidiary Genentech also started a predictive analytics project to better predict which diabetic retinopathy patients.
Likewise, Roche collaborated with IBM and Sensyne Health to use AI for predicting chronic kidney diseases and for performing clinical trials respectively.
Pfizer, America’s one of biggest multinational drug development organizations, in partnership with IBM, is rushing to fully catch up with AI technology. With the help of the cloud-based platform, IBM Watson, Pfizer is targeting on getting millions of medical data to early detect and find novel therapies for cancers.
In a research collaboration with IBM, Novartis has to spread its arms into AI to get the best outcomes and efficiently finding treatment options for breast cancers.
Using the real-time data provided by IBM’s cloud-based platform, Watson the company is deriving valuable insights related to the efficient outcomes of breast cancer treatment.
#5 Bayer Pharmaceuticals
This biggest pharma company is highly investing in emerging technologies like AI and ML to discover novel drugs for cancer and other life-threatening disorders.
As of media reports, in January 2020, the company has made a research collaboration agreement with the Exscientia to come up with the innovative drugs for cancer and cardiovascular diseases.
The company believes that the innovative AI technology can improve quality and size and reduce developing costs too. Hence, the company continues to invest in AI to achieve fast discovery and development of drugs.
Just think, these pharma and biomedicine companies are already proved their strength in the global drug development industry. Then, why they are investing in AI technology?
The simple answer is that they are trying to become more competitive and advanced in the industry. Then, why don’t you invest in AI? If not yet invested to make your processes seamless and efficient.
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