Before getting into the long list of the dramatic advantages that the two most hyped technologies of the era, namely ‘artificial intelligence’ and ‘blockchain’, has brought into the Indian pharmaceutical industry, let us have a quick look as to what these two concepts individually mean.
Artificial intelligence or AI, is defined as the simulation of human intelligence in machines that are designed to act like humans in multiple ways. The term may also be applied to any machine that demonstrates traits of human beings; such as learning and problem-solving.
On the other hand, Blockchain is a system of recording data in a way that makes it difficult or impossible to change, hack, or cheat the system. To speak further, a blockchain happens to be a digital ledger of transactions that is replicated and distributed across the entire network of computer systems on the blockchain.
Now that we know what these two tems encompasses, let us consider the various ways in which these have played their respective roles in revolutionizing the Indian pharmaceutical industry.
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Research and Innovation for Discovering New Drugs
Pharmaceutical companies across the globe, are delving deep into super advanced machine-learning or ML algorithms, and AI capacitated tools and techniques; so as to streamline the innovation of new drugs.
These intelligent tools are designed to identify intricate patterns in humungous sets of data; which can further be used to solve challenges associated with complicated biological networks. So this, becomes extremely crucial for studying the multiple patterns of various diseases and for also recognizing which drug compositions would be best suited for treating specific traits of a particular disease.
Thus, pharmaceutical manufacturing companies find it helpful and easy to invest accordingly in the discovery of such drugs that have the highest success rate of treating a disease or medical condition.
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P-Value Standards and Clinical Trial Success
P-values are a standard way that researchers measure the effectiveness of new drugs in Phase II trials in order to decide whether or not to advance the drug to Phase III. A drug that achieves a p-value of 0.05 or less in Phase II trials will typically be advanced to Phase III.
But the real process is much more complex and less predictable than what the statistical models might imply. Hence, researchers need to leverage new technologies like artificial intelligence and blockchain to enhance clinical trial design and execution.
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Drug Development
AI has been found immensely helpful in improvising the Research and Development (R&D) process for any kind of pharmaceutical drug; whether in terms of designing and identifying new molecules or target-based drug validation and discoveries, or anything else in the similar line.
As per a report prepared by the MIT, hardly around 13.8% of drugs successfully pass the clinical trials, whereas any pharma company ends up paying anywhere between US$ 161 million to US$ 2 billion for a drug to complete the entire process of a single clinical trial and get the much required FDA approval. This is why the pharma companies are increasingly moving towards AI, in order to improve the success rates of new drugs, create more affordable drugs and therapies, and above anything else, reduce the huge operational costs.
- Electronic Health Records of Patient Data
As per some reports, till a few years ago, one of the primary reasons for high death rate in India was medical errors resulting from badly coordinated care. Healthcare systems in every country are stumbling with the problem of data silos, indicating that patients and their healthcare providers have a vague idea of medical histories.
A much required solution to this problem comes in the form of a blockchain-based system of medical records connected to the prevailing electronic medical record software that acts as a comprehensive overview of a patient’s record.
It should be noted here that the actual patient data that does not go on the Blockchain. Every new record attached to the Blockchain, like a prescription, a medic’s note, or a lab result; is decrypted into a unique hash function, which happens to be a small string of letters and numbers. Each and every hash function is independent and can only be decoded by the person who owns the data.
Pharmaceutical institutes or organizations, use advanced machine learning systems to collect, process, and analyze vast volumes of patients’ healthcare data. Healthcare providers around the world are using ML technology to store sensitive patient data securely in the cloud or a centralized storage system. This is known as electronic medical records or EMRs.
- Quicker and More Accurate Diagnosis with the help of Medical Histories
Medical researchers, practitioners or doctors, refer to these records as and whenever they need to understand the impact of a specific genetic trait on a patient’s health or how a particular drug can treat a certain health condition.
Again, ML systems can use the data stored in the EMRs to make real-time predictions for diagnosis purposes and suggest proper treatment to patients. Since ML technologies have the ability to analyze and process huge amounts of data in a very short span of time, they are highly helpful to quicken the diagnosis process, and thereby help in saving millions of lives.
- Medical Data Management and Accessibility
Unfortunately, there have been multiple instances of data breaches, which resulted in the disclosure of several healthcare records. Hence, mere collection and monitoring of patient’s data is not sufficient enough, and it requires stringent regulations on privacy or accessibility.
Having said that, those records also cannot be kept within the limitations of the patients and their doctors, as multiple parties like pharma researchers, may have to access that data. At the same time, handling patient data using a traditional approach can be a complex task since this data is dispersed over different healthcare databases.
Blockchain creates a unified platform for storing and managing all relevant data in one location while preserving security and access control. Huge amount of medical data can be stored in form of blockchain blocks; identifiable through the patient’s unique ID. This process authorizes the sharing of health information or blocks without revealing the ID, in case the patient wishes to remain anonymous.
- Manufacturing of Rare Disease Preventive Drugs
Not all pharmaceutical manufacturing companies invest their time and resources on finding treatments for rare diseases; as it is, the ROI is very low, as compared to the time and cost it takes to develop drugs against those diseases.
As per a report, about 95% of the prevailing rare diseases do not have FDA approved medicines or cures. However, thanks to the innovative functions of AI and ML, pharma companies are now able to develop cures for diseases like Alzheimer’s and Parkinson’s, and a few other rare diseases.
- Epidemic prediction
Technologies like AI and ML are by now, widely in use by numerous pharmaceutical firms or healthcare bodies to monitor and predict epidemic outbreaks, anywher in the world.
Such technologies work on huge data collected from multiple sources in the web world, followed with a deep study on various geological, environmental, and biological factors acting on the health of the population of different geographical locations, and eventually connecting the links between these factors and previous epidemic outbreaks.
These technologies are extremely useful for underdeveloped economies where there is dearth of the medical infrastructure and sufficient finance to deal with an epidemic outbreak. The ML-based Malaria Outbreak Prediction Model that functions as an alarm tool, can be considered as a great example against this factor.
- Remote Monitoring
Remote monitoring is yet another breakthrough in the healthcare sector. Many pharma companies have already developed AI algorithm-powered wearables that remotely monitor patients suffering from life-threatening diseases.
For example, just by clubbing together of AI with smartphone apps, it is now possible to monitor the severity of the symptoms for Parkinson’s Disease, on the baiss of the opening and closing motions of the hands of a patient from a remote location. The frequency and amplitude of the hand movement, as captured by the smartphone’s camera, determine the severity score of the patient’s condition; thereby allowing doctors to change the drugs as well as the drug doses remotely. In case of any requirement of upgrading treatment on any worsening f the patient’s conditions, the AI sends an immediate alert to the doctor.
Remote setups like these make it convenient to dodge multiple visits to the doctor’s chamber, and saves much time.
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Higher Efficiency in Manufacturing of Drugs
Pharma manufacturing companies have implemented AI in the manufacturing process for higher productivity, improved efficiency, and faster production of life-saving drugs.
Involvement of AI has improved all manufacturing aspects like quality control, predictive maintenance, waste reduction, design optimization, process automation, and so on.
AI has replaced the time-consuming conventional manufacturing techniques, and enabled the pharma companies to launch drugs much faster, and at cheaper rates.
Apart from increasing the ROI substantially by limiting the human intervention in the manufacturing process, AI has also diminished chances of human error.
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Marketing
Like many other industries, the pharmaceutical industry is also a sales-driven one. With the help of AI, pharma contract manufacturers in India, are now finding it way easier to map customer journey. AI helps companies to see which marketing technique led visitors to their site (creating lead) and eventually converted the visitors to customers by making them purchase products from via the site. In this way, pharma companies explore and develop unique marketing strategies that promise most lead conversions, increase in revenues, along with brand awareness.
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Supply Chain Transparency for Demand Forecast
Supply chain translucency is a crucial concern, especially in the developing nations where fake prescription medicines cause millions of deaths every year. Blockchain, when paired with AI, makes it extremely easy to track each package’s end-to-end provenance, integrating with manufacturers, wholesale, shipping, etc. Apart from which once all the data gets compiled in one place, companies may use AI in forecasting demand, and optimize supply accordingly.
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Tracing down a Drug’s Authenticity
One of the major concerns in the healthcare industry is cross-checking or tracking of the authenticity of the pharmaceutical drugs or the medical supplies. Blockchain evolved as the perfect answer to this issue, as it enables tracking of the drugs to their very origin while it amalgamates all data about each of the phases of their respective lifecycles.
Every block containing drug data has a hash linked to another block and a timestamp that cannot be changed anyhow. The transactions in the blockchain are known only to the authorized parties, and the drug’s movement from one party to another is trackable in real-time.
Medical buyers or dealers get assured of the authenticity of the purchased products by scanning the QR code and accessing all the required data about the manufacturer and every other relevant supply chain parties involved. Thus making it next to impossible, for any one, to illicitly put in any fake drug.
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Cryptocurrency payments
Just like the supply chain transparency and drug traceability, blockchain has brought revolutionary change in the payment system in the healthcare industry; as it is, blockchain has enabled people to receive medical assistance and pay for them with cryptocurrency or the virtual currency in some countries. Bitcoin has already gained popularity among a few healthcare groups, as a virtual currency; for their overall payment settlements. Bitcoins are received and transferred electronically using wallet software.
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Micropayment System
A Micropayment is another idea that is a result of Blockchain. Micropayments are unique value-based models that reward patients by sticking to their doctors’ instructions and prescribed lifestyles. This transaction system functions only on a particular blockchain, and records every detail about the patient’s activities related to the treatment reexamination.