Digital Transformation in Pharma Companies – Trends for 2022

We are at a point where digitalization has become necessary for businesses to operate efficiently. The traditional approaches are no longer profitable and sustainable, and they often aren’t feasible for the organizations’ plans for growth. Pharma companies that conduct business in a highly regulated ecosystem and operate under heavy scrutiny need to evolve to remain compliant and competitive in the industry. However, choosing random technologies will create more issues instead of solving them.

Stakeholders must therefore choose innovative digital technologies for the pharma industry that can be leveraged to automate or simplify or declutter the processes and functions making them more efficient, compliant and cost effective. Which technologies are currently relevant for pharma companies? Which processes can leverage them and how? The blog details technologies trending in 2022 and how they can be used by pharma businesses to transform.

Automation in the supply chain, drug manufacturing, and redundant operations

A key component of the Pharma 4.0 revolution, automation can transform the pharma supply chain by offering reduced transactional costs to healthcare administrators. Drug quality is a serious issue that affects organizations and patients who rely on the drug’s efficacy to gain the best result from it. Automated manufacturing processes minimize manual errors arising from contaminations and other threats and help improve and maintain drug quality at much higher levels than is possible through traditional methods.

Optical Character Recognition (OCR) for document digitization, and Computerized vision in Quality control/ packaging, shipment tracking & drug traceability

OCR and computer vision have a vast scope of implementation to achieve success for the industry in its compliance efforts. Regulatory authorities often advise that the pharma organizations document every single step of the process involving drug research, clinical trials, development, and subsequent batch production for mass usage. However, the duplication arising from manual transcription and other errors often delay the process. OCR-enabled software can be used to convert user-generated documents to digital in a matter of minutes as opposed to hours spent manually. Computer visions can be used to inspect labels and barcodes while receiving the shipment to review drug authenticity and thus avoid counterfeiting. It also helps trace the origin of medicine for pharmacovigilance and adverse event management and is far less time consuming and efficient.

Blockchain for creating visibility and transparency

Communication is crucial for health professionals. Any mistakes in communicating patient data can lead to escalating expenses and may have legal implications as well. Relying on ledger-based communication enabled by blockchain can secure patient record transfer and minimize chances of miscommunication.

Artificial Intelligence and Machine Learning to detect diseases, and aid and accelerate drug discovery

Machine Learning models have been used to speed up disease detection. Using extensive diagnostic data, healthcare and pharma companies are mapping simple and effective tools that are reducing costs and time, making the screening process easier. More interestingly, this approach can be replicated for many more diseases across the world.

While selecting candidates for drug trials, selecting the right sample of candidates is crucial. But there are numerous parameters that need to be adhered to, complicating the process. Allowing Artificial Intelligence-enabled tools to assist and narrow down the subject population, can reduce timelines significantly, accelerating the drug discovery and trial process.

In fact, AI-based patents and mobile-based applications designed and developed to cater to pharma and healthcare requirements are on the rise thanks to changing legislative and regulatory systems. Active players are taking advantage of this evolving landscape by integrating these apps and leveraging wearable device data for gathering insights.

The onus lies on key stakeholders to engage with thought leaders and key opinion leaders in pharma research to understand how the new technologies can be integrated with existing systems. If the need for an overhaul is impending, it could be an opportunity to identify existing areas of lag and make the amends by implementing intelligent resource planning tools, IoT-enabled equipment, and real-time monitoring resources to plan for current and future growth priorities.