Compounding the Covid-19 impact are factors like technological advancements, an increase in the number of elderly, focus on the healthcare needs of growing countries, a rise in chronic disorders, and higher spending by pharma companies on research and development.<\/p>\n
Naturally, every player wants to make the most of the myriad opportunities present in the market. Consequently, competition among different pharmaceutical companies has been fierce. Numerous parameters are driving this intense competition within the sector:<\/p>\n
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- Greater innovation:<\/strong> Companies are competing with each other in the infectious disease landscape to drive innovation. In fact,\u00a0Covid-19has paved the way for a\u00a0multi-billion <\/a>dollar vaccine market.<\/li>\n
- Value-driven care:<\/strong> Some companies are competing on customer experience, with organizations going above and beyond their call of duty. For instance, Eli Lilly, an American pharmaceutical company, is offering support to its diabetic patients who have lost their jobs or their insurance policies due to Covid-19.<\/li>\n
- Change in operations:<\/strong> As per\u00a0a recent McKinsey report<\/a>, there is a fundamental change in pharma operations. Covid-19 has forced companies to be more open-minded, transparent, and agile. There is also a greater focus on improving network risks, both within and outside the workforce.<\/li>\n
- Increased transparency:<\/strong> While the traditional-and-highly-regulated pharma industry has always been slow to embrace emerging technologies, the ongoing pandemic has changed the equation. Today, pharma brands are increasingly investing in deploying digital and AI-driven analytical tools to boost transparency across key areas such as drug development, marketing, manufacturing, and so on.
\nA recent report by\u00a0Deloitte <\/a>indicates that 75% of large organizations\u2014those earning more than US$10 billion in revenue every year\u2014invested over US$50 million in AI projects\/technologies. Even smaller organizations\u2014those with annual revenue of US$5-10 billion\u2014follow the same trend; 95% of such mid-sized organizations invested up to US$50 million in 2020.<\/li>\n<\/ul>\n![\"artificial](\"https:\/\/news.sap.com\/india\/files\/2022\/06\/03\/75_1200X271.jpg\")
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- Increased drug spending:<\/strong> According to a new\u00a0report<\/a>, a total of 300 new drugs are expected to be launched over the next five years by 2026. This is much higher than the number of new drugs launched in the last decade. Demand too is expected to see a rise\u2014the global spending on medicines is expected to grow at a CAGR of 3-6%. While this may seem paltry, here\u2019s the real deal\u2014spending is expected to reach about $1.8 trillion by 2026. This is in addition to the spending on Covid-19-related vaccines and booster shots.<\/li>\n<\/ul>\n
If competition is going to be the bedrock of growth in the near future, then\u00a0artificial intelligence\u00a0will play a crucial role in determining which pharma brands stay ahead of the pack.<\/p>\n
How AI is Helping Pharmaceutical Companies to Stay Competitive?<\/strong><\/h2>\n
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Artificial Intelligence can improve the drug discovery process:<\/strong><\/h3>\n<\/li>\n<\/ol>\n
Pharma brands are leveraging the power of AI to aid the relatively expensive and competitive drug discovery process. AI solutions can successfully identify disease patterns in large datasets and help understand which drug compositions would be best suited for treating different diseases. For example, the MIT-industry consortium, ‘Machine Learning for Pharmaceutical Discovery and Synthesis<\/a>‘, which\u00a0comprises top<\/a>\u00a0pharmaceutical giants such as Bayer, Lilly, Novartis, Pfizer, etc., uses MIT\u2019s robust machine learning solutions to improve the drug recovery process. This can:<\/p>\n
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- Help efficiently access and analyze vast amounts of chemical data to ultimately improve business processes and outcomes<\/li>\n
- Provide critical insights into how to improve the designing, optimizing, and synthesizing of drugs<\/li>\n<\/ul>\n
More recently, GSK\u00a0partnered<\/a>\u00a0with Vir Biotechnology to leverage artificial intelligence for identifying antiviral compounds that can treat coronaviruses, including Covid-19.<\/p>\n
By embracing AI solutions, pharma companies are actively working on lowering R&D costs, preventing human errors, and accelerating the research timeline\u2014leading to affordable-yet-profitable drugs.<\/p>\n
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AI can help in the process of drug development and production by making it more effective:<\/strong><\/h3>\n<\/li>\n<\/ol>\n
Did you know that only 14% of all drugs in clinical trials win approval from the FDA, as per research by\u00a0MIT<\/a>? That is a poor outcome for clinical trials that can cost around\u00a0$1 billion<\/a> for each newly approved\u00a0drug. This means the drug approval process can turn out to be a costly affair if the drug does not get approved. This is where AI can play an instrumental role in improving\u2014and optimizing\u2014the drug development process. Artificial intelligence tools can improve the success rate of new drugs by:<\/p>\n
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- Performing quality control and ensuring high-quality standards<\/li>\n
- Driving increased automation of daily core workflows<\/li>\n
- Fixing supply chain issues within the production line and reducing wastage of materials<\/li>\n
- Enhancing the production reuse value<\/li>\n
- Performing predictive maintenance and reducing operational costs<\/li>\n
- Forecasting demand and supply changes<\/li>\n<\/ul>\n
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AI can provide diagnostic assistance and empower physicians to deliver personalized treatment<\/strong><\/h3>\n<\/li>\n<\/ol>\n
At the heart of personalized treatment lies real-time patient data. AI-powered solutions and machine learning technology can empower healthcare brands to:<\/p>\n
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- Embrace a data-driven approach and analyze volumes of patient data<\/li>\n
- Set up an electronic medical record system, whereby healthcare enterprises can store sensitive patient data on secure cloud platforms<\/li>\n
- Drive customized treatment options in real-time by enabling doctors to look at historic patient data, previous diagnostic tests, etc.<\/li>\n
- Successfully diagnose issues. For instance, recently, the\u00a0FDA <\/a>authorized the marketing of an AI-drive platform\u2014GI Genius\u2014which can assist clinicians in detecting signs of colon cancer. This medical device leverages machine learning and AI algorithms to look for potential lesions in real-time during a colonoscopy.<\/li>\n
- Engage in remote patient monitoring using AI-powered wearables, which is especially useful in times of a global pandemic. Such is the popularity of remote patient monitoring (RPM) devices that the global RPM systems market is projected to be worth over\u00a0$117.1 billion <\/a>by 2025.Here is a real-life example:\u00a0Chinese tech giant\u00a0Tencent teamed up<\/a>\u00a0with a London-based healthcare firm, Medopad, to develop an AI software that can reduce the diagnosis time for Parkinson’s Disease from 30 minutes to 3 minutes. This is achieved by looking at the existing video footage of patients and using video analysis to promote early diagnosis, successful screening, and accurate daily evaluation of key functions.<\/li>\n<\/ul>\n
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Artificial Intelligence can help predict epidemic outbreaks<\/strong><\/h3>\n<\/li>\n<\/ol>\n
Machine learning models are being used to predict\u2014and prevent\u2014epidemics such as Malaria. According to a\u00a0study<\/a> conducted in Maharashtra, a data mining classification algorithm\u2014Support Vector Machine (SVM)\u2014was used to successfully predict the onset of malaria in the early stages with a lower error rate. This type of AI\/ML tool can empower organizations to engage in early preventive care and put the right measures in place to combat it. Here\u2019s how AI can assist in epidemic prevention:
\nStep 1:<\/strong> The AI\/ML tools feed on real-time information that is gathered from disparate sources across the web.<\/p>\nStep 2:<\/strong> The predictive tool studies a multitude of environmental, biological, and other factors to make connections with previous epidemic outbreaks and provide relevant patterns, trends, and solutions.<\/p>\n
Another excellent example <\/a>of predictive forecasting is GlaxoSmithKline\u2019s use of AI to promote its seasonal medicines in the Allergy Cold and Flu category. The brand leverages a predictive model that helps chart how the upcoming season for allergy or cold and flu will shape across varied geographical regions; including where it may peak and where it may lag. This empowers the brand to:<\/p>\n
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- Inform consumers about the upcoming flu season through their website<\/li>\n
- Enhance the national and regional media delivery<\/li>\n
- Keep the retailers informed of key factors such as seasonal distribution, stock up, display, etc.<\/li>\n<\/ul>\n
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AI can enable pharma companies to \u2018sell and market\u2019\u00a0better as well as smarter<\/strong><\/h3>\n<\/li>\n<\/ol>\n
Considering that the pharma industry is inherently sales-driven, pharma companies can leverage the power of Artificial Intelligence in driving a more targeted and personalized marketing campaign. AI tools can be used to:<\/p>\n
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- Collect customer data in real-time, map out the customer journey and understand the customer\u2019s needs, preferences, behavior, etc. better<\/li>\n
- Curate unique marketing strategies that are aligned with the customer\u2019s\u00a0distinctive needs as well as the company\u2019s\u00a0business goals<\/li>\n
- Measure the efficacy of marketing campaigns and analyze key performance indicators conversion rates, retention rates, etc.<\/li>\n
- Analyze previous marketing campaigns and engage in a comparative analysis, to eliminate any inefficiencies in existing strategies. It can also help predict the success rate of marketing campaigns<\/li>\n<\/ul>\n
AI tools can also be used to learn about in-store\/online customer behavior. For instance, GlaxoSmithKline uses AI for tracking the eye movements of consumers and retailers (with their consent). The brand studies this data\u2014collected using special\u00a0eye-tracking glasses worn by shoppers in stores or\u00a0online\u2014in its dedicated shopper\u2019s science lab, thus, enabling it to\u00a0monitor\u00a0how the end-user looks at the products. The AI-powered tool captures key images during the shopping process and provides analysis for Areas of Interest (AOI) metrics such as the time to first fixation, heatmaps, gaze plots, video replays, etc. This invaluable data can be used to engage in better product placement, improve the artwork and labeling of products, and discern consumer behavior from the inside out.<\/p>\n
![\"AI](\"https:\/\/news.sap.com\/india\/files\/2022\/06\/03\/Role_of_Ai_1200X977.jpg\")
<\/p>\nThe writing is on the wall<\/strong><\/p>\n
It is the day and age of\u00a0Artificial\u00a0Intelligence. Almost no industry is untouched by AI, and the pharmaceutical industry is no different.<\/p>\n
AI\u00a0today finds application in nearly every aspect of the pharma product lifecycle.\u00a0So naturally, the use of artificial intelligence in the pharma industry is not going to slow down any time soon. In fact,\u00a0research<\/a>\u00a0suggests that 50% of global healthcare companies will actively execute AI strategies and adopt this futuristic technology by 2025.<\/p>\n
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- Engage in remote patient monitoring using AI-powered wearables, which is especially useful in times of a global pandemic. Such is the popularity of remote patient monitoring (RPM) devices that the global RPM systems market is projected to be worth over\u00a0$117.1 billion <\/a>by 2025.Here is a real-life example:\u00a0Chinese tech giant\u00a0Tencent teamed up<\/a>\u00a0with a London-based healthcare firm, Medopad, to develop an AI software that can reduce the diagnosis time for Parkinson’s Disease from 30 minutes to 3 minutes. This is achieved by looking at the existing video footage of patients and using video analysis to promote early diagnosis, successful screening, and accurate daily evaluation of key functions.<\/li>\n<\/ul>\n
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- Value-driven care:<\/strong> Some companies are competing on customer experience, with organizations going above and beyond their call of duty. For instance, Eli Lilly, an American pharmaceutical company, is offering support to its diabetic patients who have lost their jobs or their insurance policies due to Covid-19.<\/li>\n