Artificial intelligence and Machine Learning present the pharma industry with various opportunities to substantially improve the pace of drug discovery and distribution process. The current protocol followed needs to be upgraded in order to meet the rising demand for medicine and that too without compromising its quality. These technical advancements will help the pharma companies to process the structured and unstructured data in order to derive useful and actionable insights. Application of Machine learning and AI into drug discovery will not only accelerate the process but also help the companies to spawn a higher return on investment. It will make it easier for the scientists to find the potential targets and for the manufactures to ensure its timely delivery. McKinsey estimates that machine learning and big data can help to generate a profit of around $100billion for the pharma industry. The insights produced with the help of analytics would help the pharma companies to take better decisions, improve the efficiency of clinical trials, advance the shipping process and ultimately achieve greater commercial success.
Look how ML and AI are transforming the pharma industry and making it even better than before.
Supply Chain Management
Optimization of the supply chain across pharmaceutical industries has always been a challenge for the owners. However, with the advent of AI and ML the process is becoming smoother. The big data generated helps companies to reach out to their prospective clients and understand their needs, which in turn ensures the number of drugs to be produced by the companies. Also, predictive analytics insights generated with the help of big data allows the companies to foresee the demand pattern and hence manufacture only the required quantity of medicines. The drugs today are being increasingly customized for even small populations with particular genetic profiles. Finding out a way to deliver a medicine which is relevant only to a small bunch of 1000 people is more difficult than delivering medicines across the world. This venture requires proper utilization of resources so that there is no delay in delivery and loss to the company. An expert at “LogiPharmaUS Conference” 2017 said that “Instead of executing one supply chain a thousand times, we should get ready to execute a thousand supply chains, one at a time.” This act will not only ensure timely drug delivery but also safeguard the hassle of re-execution every time. Machine learning and AI algorithms can help to automate this process and make it more robust.
Now, when we talk only about shipping the drugs, there are many medicines that are expensive and require very specific conditions to be transported. Billions and trillions of money are spent by the pharma companies to deal with the transportation process. With the application of ML and AI the pharma companies will be able to forecast the demand and distribute the products efficiently. Also, many key decisions will become automated allowing the companies to cut down their labour costs and make more profit.
Unlike other products, manufacturing of drugs require more attention. The temperature, pressure, fermentation time etc. all have to be kept in check so that the vaccines/drugs that are being produced meet the market standards and offer the desired results. If even one condition is disrupted, the entire batch has to be discarded which accounts for a huge loss in money as well as labour for the companies.
With the help of machine learning and artificial intelligence, pharma companies are able to identify the characteristics that may stand responsible for drug’s degradation. For instance, Merck has placed a data-collection technology to “identify the root cause of batch non-confirmation issues” which has compared the batches over 5.5 million times. By doing this the professionals have been able to identify the early fermentation phase of vaccine production that serves as a strong predictor of the quality of vaccine. Thus these advanced analytics algorithms allow the pharma industry to meet the strict quality standards without making any compromise. Also, the data from the previous batches helps to understand the key factors that may have been responsible for the failure of drug formation in previous cases. This insight helps the company owners to ensure that no such errors/mistakes are made in the future that may hamper the drug’s quality.
Reshaping Research & Development
A drug takes around 12 years to reach the market, during this time it undergoes various processes: target identification, drug formation and clinical trials. Out of these identifying the target is what consumes the maximum time of the scientists. The disease-causing organisms keep on evolving rapidly and hence their genetic make-up changes as well. This makes it challenging for the scientists to find targets against which inhibitors have to be designed. Earlier the scientists had to go through a lot of literary studies to identify the patterns and then create a hypothesis on which the research could be based. With the advent of machine learning and artificial intelligence, there are ways in which scientists can retrieve the sequenced genes and run them against each other to predict conserved domains (potential targets). These predicted targets can then be used to create drugs against them. All the process that use to take years of hard work is now just a few clicks away. This not only speeds up the process of drug creation but offers other insights related to the disease as well. Talking the other way around, AI and ML may also assist companies to foretell the chemical compound that may be used against the predicted targets.
An Ending Note
After around 100 years of advancements in medical science, life’s expectancy and quality have surely been improved. But somehow now, the pharma industry is witnessing a stagnant growth, probably because a larger number of drugs need to be manufactured and reached out to the patients all over the world. At DataToBiz the professionals focus on helping the pharma industry to improve their logistics and manufacturing components. They can help the industries to keep a track of their shipment so that medicines reach the public on time. The experts may also assist the pharma industry by utilizing all their previous data and predicting the demand patterns of a certain medicine prior to its production. All these methods will not only help the pharma industries to create quality products but also assist them in efficiently distributing them all over the globe. If you have any queries regarding their work, feel free to contact