Today, we can enjoy innovations that were once considered science fiction, thanks to Data Science. Machine Learning (ML) and Artificial Intelligence (AI) have revolutionized the industry, enabling advancements such as virtual assistants, self-driving cars, smart homes, chatbots, and surgical bots etc.
Tractica projects that the global artificial intelligence software market will grow from $10.1 billion in 2018 to $126 billion by 2025. Companies across all industries are using Artificial Intelligence and Big Data technologies, including the pharmaceutical industry, in an era of data-driven business.
Top challenges that the Pharma industry faces
The pharma industry is at a rapid pace of development. However, certain challenges halt its exponential growth. Let’s have a look at them –
- Need for development of new drugs
Though the pharma industry has already developed extensive cures, it is becoming more difficult to fight certain diseases. Top researchers and scientists still can’t completely cure diseases such as COVID-19, SARs, MERS, etc..
- Customer expectations are rising
There is a lot of commercial competition in the pharma industry as consumers become more aware and knowledgeable. The more successful pharmaceutical companies become, the bigger are their problems. Now, customers want better drugs, no adverse effects, and lower prices. The patients also wish for more affordable treatments, therapies, and medicines.
- Treatment of incurable diseases
It has always been a challenge for the pharmaceutical industry to find cures for incurable diseases like Cancer, Alzheimer’s, and Epilepsy. A quick solution is rare, and research and development take time.
- Complex Intellectual Property rights
Intellectual property rights and patent protection are still difficult to enforce in developing countries. Furthermore, a number of markets subsidize generic drugs, creating obstacles for research-focused companies.
AI & ML has the power to transform Pharma industry
A lot of untapped opportunities for business transformation exist with AI in the pharma industry. Big data and AI-powered analytics have brought about a radical change in the way innovation is done. AI has the potential to foster innovation, improve productivity, and deliver better results across the value chain. Through innovation and the creation of new business models, AI can make a significant difference in the value proposition of pharma companies.
McKinsey says machine learning in pharma and medicine will allow better decisions, optimal innovations, improved patient outcomes, improved clinical trial efficiency, and provide new tools for physicians, consumers, regulators, and even insurers. In fact, they estimate that this technology could be worth up to $100B annually.
The drug discovery process is being significantly accelerated by leveraging industry 4.0 technologies such as Natural Language Processing (NLP), Machine Learning (ML), Artificial Intelligence (AI), evolutionary algorithms, IoT, and wearables.
How is AI/ML supporting R&D through predictive analysis?
Pharma R&D powered by AI delivers predictive analytics that allows researchers to identify diseases with great precision and a high degree of accuracy. In addition to providing in-depth insights and data necessary for validating and testing drug concepts, it also optimizes treatment delivery methods.
Usually, the cost of researching, testing, perfecting, and validating a drug concept can reach $2 billion. Costs can be reduced, however, if drug candidates can be accurately predicted, which increases the chances of clinical trial success.
Analytics powered by AI can help researchers eliminate trial and error in the drug discovery process, allowing them to present more viable solutions for FDA approval more often. Ultimately, this results in lower R&D costs.
Applications of AI/ML in Pharma industry
Here are some new age applications of AI/ML in the pharma industry –
Disease Identification/Diagnosis
With the ability to quickly analyze large amounts of data, ML technologies can assist in accelerating the diagnosis process, helping save millions of lives.
Digital Therapeutics / Personalized Treatment / Behavioral Modification
As a diagnostic tool, it can be effectively used to identify individuals with early insights into the condition – include gum health, accurately classify cutaneous skin disorders, and suggest primary treatment options with OTC medicine, which may augment the clinical diagnostic capabilities of clinicians as well as improve the decision making of your child’s teacher, therapist or physician.
Drug Discovery and Manufacturing
AI can increase productivity, increase efficiency, and speed up production of life-saving drugs for the pharma industry. In the manufacturing process, AI can manage and improve all the following areas:
- Quality control
- Predictive maintenance
- Waste reduction
- Design optimization
- Process automation
Aside from reducing the time-consuming process of conventional manufacturing, AI can help pharma companies launch their drugs into the market faster and at a lower cost.
Predictive Forecasting (e.g., Epidemics)
Healthcare providers and pharmaceutical companies are already using AI and ML to track and predict outbreaks worldwide. They analyze data gathered from disparate sources on the Web, investigate the links between unrelated geological, environmental, and biological factors and previous epidemic outbreaks, and try to connect these dots.
Clinical Trial Research
Artificial intelligence can be employed in clinical trials to identify patients who fit the trial requirements. A clinical trial can be determined by analyzing genetic information with advanced predictive analytics. In these trials, AI is also helpful for determining the ideal sample size.
Smart Electronic Health Records
A greater emphasis on patient-centric care can only be achieved through smarter and more efficient EHR systems. Pandemic effects have prompted the need for telehealth compatibility in EHR systems, as well. It can even offer tailored recommendations to doctors and develop unique treatment plans using the same information.
AI/ML secures the future for global pharma companies
The Internet of Things, blockchain technology, and artificial intelligence all play a role in the evolution of healthcare systems. Biotech and pharma companies are taking advantage of these technologically advanced solutions to provide solutions for various stages in the product lifecycle, including drug discovery, clinical trials, manufacturing, regulatory approval, pharmacovigilance, and marketing.
The term “PharmaTech” refers to the use of technology in R&D processes. A good way to put it is that PharmaTech refers to several ways that new technologies can assist companies with various aspects of the work required in pharma research and development. Researchers, industry, and regulators are finding new ways to advance existing technologies in order to deliver better and more user-friendly healthcare.
By improving R&D, AI also helps companies differentiate their products and deliver healthcare solutions to hospitals and patients more quickly than before. Increasing clinical trial success rates lowers R&D costs, increasing profit margins for pharma companies.
In-market success can be achieved through optimizing medication adherence and treatment outcomes by integrating IoT and AI. Additionally, the tech can boost pharma sales productivity and revenue.
Reps’ productivity and turnover can be dramatically impacted by AI-driven pharma sales software. By analyzing industry trends and customer preferences, the technology can figure out what kind of treatment the doctor prefers, for instance.
This intelligence may be used by sales teams to prepare informational and promotional material for pre-calling. Lead conversion rates increase when pre-meeting preparation is done well. Revenues for pharma companies can increase as a result.
Benefits & improvements in Pharma landscape using AI/ML
By using data mining and analytics, engaging patients, monitoring compliance, and making efforts, pharmacy artificial intelligence can support revenue growth and operational efficiency. It can affect your R&D time and costs, too!
Rapid drug research and development is one of the most significant benefits of AI in the pharma industry. In this process, machine learning (ML) and deep learning (DL) algorithms are used to “train” computer systems to automate the process of acquiring and analyzing massive amounts of raw genotypic and phenotypic information relevant to drug development.
By using the system, big data collected from Internet of Things (IoT) devices (such as wearable health monitoring), journal articles, patient management software, and other public and private databases is streamlined and fast-tracked.
Using AI systems that assemble R&D data automatically and relatively quickly can shorten the time it takes to discover a new medicine, which is longer with a human-centric approach. By delivering new drugs to hospitals and patients at a comparatively fast rate, drug producers can increase their speed to market and gain a competitive advantage.
The pharma industry has innovated on multiple levels:
- Screenings and diagnoses: Making better use of existing data to extract information from images such as MRIs and mammograms.
- Biomarkers: Using physiological monitoring data in developing new biomarkers, for example, in the treatment of central nervous system disorders.
- Therapeutics: Monitoring a patient’s progress during treatment while adjusting drug dosages based on the progress of the patient.
- The Real World Evidence: It is the analysis of post-market data regarding safety, usage, comorbidities, and other factors not captured by clinical trials.
Conclusion: AI/ML is a big value driver for modern Pharma
Innovative tools and technologies have long been used in the pharma industry to help deliver safe, effective drugs to consumers. It would seem that the recent pandemic is merely a race against time for manufacturers to find a viable vaccine, but the use of digital technologies and tools has enabled the pharma sector to achieve this historical victory. AI/ML has played a crucial role in the way industry has modernized and delivered impactful outcomes. The new age tech has radically changed the way scientists develop new drugs, treat diseases, and much more for the last five years. As per a verdict report, 70% of the businesses surveyed believe that AI will be important for their survival and growth. The importance of this statistic cannot be overstated for pharma companies that thrive on innovation. AI/ML has turned out to be a great value driver for the pharma industry and will continue to do so for years to come.
Article by Sundeep S Reddy, Principal Data Consultant at Gramener