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 & benefits of artificial intelligence in pharmaceutical industry. 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.

Robotics Surgery

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.

Click here to know how to implement and use Artificial intelligence in drug discovery and AI 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.

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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.

#3 Pfizer

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.

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#4 Novartis

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.

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#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.

Conclusion

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 or artificial intelligence in pharmaceutical manufacturing?

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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Artificial Intelligence (AI) is a rapidly growing technology that is used for a wide range of applications across industries. Small, mid-sized, mid-sized, and multinational companies are using AI technology and enhancing their capabilities to work smart in this digital sphere.

Like retail, e-commerce, and manufacturing sectors, AI is gaining prominence across healthcare and pharma sectors. Leveraging the power of this modern Artificial Intelligence in Pharma Industry, the companies are finding innovative ways to resolve some of the significant issues that the pharma sector is facing today.

Yes. AI-powered apps using machine learning, deep learning, predictive analytics, and big data have brought a radical shift in the paradigm of pharma.

Artificial intelligence in Pharmaceutical Industry has the potential to promote innovation, while at the same time increasing productivity and providing better results. In addition, Artificial Intelligence in Pharma Industry offers a value proposition to the companies by creating new and latest business models.

You can observe AI implementation in almost every aspect of the pharmaceutical field. From drug discovery and development to drug manufacturing to supply chain and marketing, AI has its impact. Hence, AI in Pharmaceuticals and Healthcare ensures cost-effectively operations, business efficiency, and hassle-free approvals for new drugs. We learn more about benefits of artificial intelligence in pharmaceutical industry as well.

In this article, we would like to give you a brief overview of the top 10 AI applications in the pharmaceutical sector. These best AI trends & use cases in pharma will let you understand the rapid AI adoption in pharma.

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The Best Applications Of Artificial Intelligence In Pharmaceutical Industry

#1 Drug Discovery Process and Design

The use of AI in the pharmaceutical industry for the design and development of drugs is increasing. From making small molecules to determining novel biological targets, AI plays a prominent role in drug target identification and validation. It is widely used for multi-target drug innovation and biomarker identification in an efficient way with great accuracy.

A major benefit of the pharma industry is that when AI is administered during drug testing, it minimizes the drug development time. Artificial Intelligence in Pharma Industry will also benefit drug developers to accomplish clinical trials faster and launch their products into the market for use. It leads to a cost and time-saving development process and also makes the innovative drugs available for improving patient care without side effects.

For example, researchers in pharmaceutical can identify and verify novel cancer drugs using data such as longitudinal EMR records (Electronic Medical Records) and other omic data. The AI systems using ML and other data analytics algorithms will extract insights from EMR data and creates the best formulations to design and develop drugs that cure tumors well.

#2 R&D

Pharma companies across the globe are using advanced AI-powered tools and ML algorithms to smoothen the drug research, development, and innovation process. These technology tools are designed to detect complex patterns in large datasets. Therefore, AI in pharma industry can be used to resolve problems associated with the research and development process.

This ability to study patterns of various diseases and to determine which composite formulations are best suited for the treatment of specific symptoms of a particular disease is excellent. Pharma industries can invest in the R&D of such drugs that are more likely to treat a disease or medical condition successfully.

#3 Disease Prevention

Pharmaceutical organizations can use Artificial intelligence to develop medicines Parkinson’s and Alzheimer’s and very rare diseases.

As per Global Genes, it is a fact that almost 95% of rare diseases do not have more drugs to treat and cure faster. However, thanks to the innovative capabilities of AI and ML. The use of AI in the pharmaceutical industry will completely transform this scenario and ensure the most-advanced models for detecting hazardous diseases in the early stage and improve patient outcomes.

#4 Next-Level Diagnosis 

Physicians can use advanced machine learning systems to gather, process, and analyze patient health care data. Healthcare professionals across the globe are using deep learning and ML to securely store patient data in the centralized storage system or cloud. It is called Electronic Medical Records (EMR).

Physicians may refer to these health records when they need to understand the effect of a specific genetic trait on a patient’s health or how medicine treats it. Machine Learning systems can use data stored in EMRs to generate real-time estimates for diagnostic purposes and to indicate appropriate treatment for the patient.

As ML technologies are capable of processing and analyzing large amounts of data quickly, they can help speed up the diagnostic process, thereby saving millions of lives.

#5 Epidemic Prediction

Pharma companies and healthcare industries are using ML and AI technologies to monitor and assess the spread of infections worldwide. These modern technologies are used for consuming data collected from various resources, analyzing several environmental, biological, and geographical factors on the population health of diverse geographical regions, and deriving data insights to reduce the impact of epidemics in the future.

Artificial intelligence and machine learning models are particularly beneficial for underdeveloped economies that lack medical infrastructure and financial framework to combat the spread of infection.

A good example of this is the ML-based malaria outbreak prediction model, which serves as a warning tool for malaria outbreaks and helps health care providers take the best action to combat it.

#6 Identifying Clinical Trials 

It is one of the key pharmaceutical use cases for embracing AI into existing models. The use of AI in the pharmaceutical industry for identifying drug candidates which are under final clinical trials from vast clinical data is on the rise.

Artificial Intelligence in Pharmaceutical Industry will help companies in analyzing thousands of samples in minutes and automatically logs data related to how patients are responding during clinical trials.

Here are a few advantages of using AI in pharma industry for clinical trials:

• AI applications or systems analyze historic clinical data
• AI apps help in monitoring drug performance and evaluating drug responses
• With the integration of speech recognition technologies, AI apps for pharma will be helpful for recording patients’ oral text during drug trial phases. It means that AI applications will record patients’ responses.

Hence, the use of artificial intelligence in clinical trials has the potential in fastening clinical trials and introduce the safest drugs into the market. It is also one of the top use cases for Machine Learning in Pharma. Speech analysis and real-time patient and drug monitoring activities will be done accurately using ML, deep learning, and natural language processing technologies.

#7 Drug Adherences and Dosage

The adoption of AI in Pharmaceuticals and Healthcare is increasing at a rapid pace for identifying the right amount of drug intake to ensure the safety of drug consumers. AI technology will monitor patients during clinical trials and suggest the right amount of dosage at regular intervals.

These are all key pharmaceutical use Cases for Embracing AI. AI in Pharmaceuticals and Healthcare will definitely accelerate automation in processes and drive more accuracy than ever before.

These AI trends & use cases in pharma will assist drug development and healthcare companies in ensuring efficacy across end-to-end production lines and delivering top-notch performance in front of the FDA.

Conclusion

The scope of Artificial intelligence and machine learning in the Pharma industry looks very promising in the future. AI opportunities for pharma companies are unmeasurable.

The use of AI applications in pharma will ensure operational excellence across drug structure design, drug development processes, selecting patients for clinical trials, monitoring drug performance, identifying proper dosage, etc.

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