Digitization in Pharma - Risk or Opportunity?

1. The Big Picture: Digitization of Pharma – Is it at Pace?

Globally, all industries are embracing digitization for operational efficiency. They have already gained benefits from this evolution. Is pharma catching pace with other industries? The answer is a big NO. As late as 2017, when a survey was conducted in Germany, pharma was ranked at the bottom of the list in the Digital Index scale.

I came across a meme – Why did the pharma company cross the road?

To catch the cloud eventually… after they finish their paperwork.

That’s the level at which pharma is progressing. The executives in pharma were quite cautious in adopting the digital revolution. However, the scenario has started changing now.

There is a saying: who survives, the strongest or the intelligent? The answer is the one who adapts to the changing situation. In this digital revolution, if you don’t adopt, you will be left behind.

There are various reasons behind adopting digitization. In a global corporate survey conducted in 2022, 86% of the executives believed that they lack skilled workers in pharma. That’s leading them to adopt automation and digitization.

Global and Indian regulatory bodies are pushing for controls over data integrity, automation of processes, digital documentation, and reducing human interventions. That sets the pace for pharma to catch up. The trend is very positive.

This sets up the urgency and relevance of the topic, especially post-COVID, when remote audits, digital traceability, and real-time quality oversight became non-negotiable.

2. Industry 4.0: Digital Revolution

Industry 4.0 considered several digital technologies that would take over the digital revolution. They were process automation, augmented reality, virtual reality, wearables, and digital twins, etc. The latest in the series is artificial intelligence.

Integration of digital technologies in development to manufacturing, to distribution brings innovations, improvement in quality, efficacy, and agility to the pharma industry.

These innovations help with the faster introduction of products into the market. That helps patients to get the benefit of new products much earlier. Even with this knowledge, pharma is not at the pace of other industries. That’s due to the documentation, compliance, deviations, and audits. The risk is that any failure in these processes can cause a major impact on patients. When there are any failures, the fear of rejection of the product by the regulatory agencies makes pharma more cautious in moving to newer technologies.

Digitization will be useful to debottleneck the processes, reduce waste and errors, identify potential risks in the system and avoid them rather than react to them, increase visibility in operations, and provide greater agility and higher quality that gives a competitive edge.

3. The Case for Digitization in Pharma: India and the World

Global pharma companies have started adopting automation and digitization. Major pharma companies have already adopted automated warehouses, digitized material management, automated manufacturing processes, and introduced software for quality control and quality assurance processes.

A survey conducted by Gartner, US, concluded that 91% of employees say that improving digital dexterity improved their work effectiveness. 40% of executives believe that digitization improved their operational efficiency.

The approach by global regulatory agencies has also changed. They believe that automation and digitization tools should be seen as drivers of quality. USFDA recognizes that digitization is increasingly becoming the standard of modern manufacturing environments.

Digitizing, in fact, provides better traceability and regulatory alignment. Global pharma companies are adopting advanced digital stacks. J&J demonstrated that its warehouse automation using robotics reduced order fulfillment time by 30% and reduced labour cost by 25%.

While in India, several companies are exploring automation and digitization, they are still relying on hybrid or paper-heavy systems.

Drug regulatory bodies like the USFDA and the Indian drug monitoring agency, CDSCO, are recognizing the digitization tools. Even though they don’t endorse them, they appreciate the efforts in digitization by companies.

4. What Digitizing Pharma Actually Means

Digitization is speeding up the lifecycle of a product and helps to get to market faster. It contributes to each of the departments involved in the product—from R&D to logistics.

The latest sensation in digitization is artificial intelligence, commonly called AI. This tool is making the process much faster and close to accurate.

In R&D, AI tools and digitization provide a better understanding of the process and can predict the best possible route of synthesis/manufacturing that can provide an efficient process with low impurity profiles. Even today, getting a competent R&D scientist is a challenge, and that is now overcome with AI predictions of the processes.

Manufacturing is made easy with real-time monitoring, alerts, and automation that reduces or avoids rejections otherwise caused by a lack of training or negligence. This leads to improved quality and efficiency.

Going with QR codes made life easy for the warehouse. QR codes automatically change the status from quarantine, approved, and rejected, which helps warehouse managers address the issues of moving materials as and when the status of the material changes. This also saves space and makes the process error-free, otherwise caused by human errors.

It optimizes inventory management and reduces cost.

Cleaning validation was a very high-profile activity managed by very experienced personnel. With automation software in place, this process provides more authentic outcomes and is error-free, avoids revalidation, and hence reduces the cost.

Even in QA, several automation software like QMS, document management, and training management have made the process very easy, and decisions are taken more confidently due to digitization.

Even the logbooks and stability software have made the process more efficient with less human dependency. E-logbooks helped minimize the documentation into multiple logbooks. Similarly, the stability software predicts the behaviour of the product, which leads to early decision-making and conclusions.

AI-driven decision-making is making investigations more effective. However, it may not beat some of the best brains in decision-making.

Clinical trials would have been a nightmare until you got the results out. But the eClinical trial programs provide real-time monitoring, sample collections, and track variables online so that you get to know the outcome sooner.

The logistics solutions were the first ones to enter pharma due to their limited intervention with the quality process. These logistic solutions adopt multiple variables to achieve better outcomes that save money and time. In fact, the logistic solution, along with serialization, tracks the product to the level of consumption by patients.

Targeted treatment—with AI and machine learning, we are now able to prescribe medicine specifically to a patient for selective cure.

The cloud base has brought agility in monitoring the processes from anywhere.

AR/VR defined a different way of handling virtual inspections during the troublesome COVID period, which is still being used efficiently today.

Digital twins are another digitization tool that has made predictive maintenance possible. That avoids breakdowns and improves efficiency. It helped in reaction processes where you can simulate and tweak the process with real-time input of information to achieve a better outcome without touching the original reactors, thereby avoiding rejections and achieving a better process in much shorter time.

Digital twins are also used in clinical programs wherein they provide biofeedback and medical intervention much earlier. In fact, digital twins were used by NASA way back in the 1960s when one of their space stations had an oxygen supply issue. They used digital twins on Earth and tweaked the process to optimize oxygen use, thereby bringing the scientist back safely.

Digitization is not just scanning documents. A user must be careful while evaluating any software—it should not be just another Excel sheet presented in a more visually appealing way. Digitization is collecting data, analyzing it, and deriving conclusions from it.

AI in pharma – Major analysis wings have predicted that 60% of executives will move into AI-based decision-making by 2027. A major company like Parexel has demonstrated that AI-based tools helped them reduce the time for preparing drug safety reports to 30–40 minutes.

5. The Human Barrier: Why Digitization in Pharma Often Takes Longer

As discussed earlier, digitization in pharma takes a longer timeline compared to other industries. The major reason is neither regulations nor complexity in the pharma process. It’s not a surprise that the major barrier is the human factor. Common hurdles in Indian and global pharma plants are:

Lack of training, digital fatigue, and fear of non-compliance from systems. Expecting automation to match the current paper-based system and hence maintaining the complexity of the system. Over-customization of tools leading to underutilization. Not testing all scenarios during the trial phase and later raising concerns once implemented. Inadequate change management and CSV burdens.

6. What Works: A Practical Implementation Roadmap

Define the requirement and implement only those process digitizations. Get into the details of the digitization/automation system carefully and understand the full scope of what’s available. Adopt phase-wise implementation, like initially QMS system, DMS, LMS, and integration with MES. Understand the system and align the SOP accordingly. Adopt training, ownership, cross-functional buy-ins, and move on to a train-the-trainer model. Modular cloud-based systems are preferred for scale and affordability.

7. Regulatory Perspective of Digitization, Automation, and Artificial Intelligence

USFDA, EDQM, as well as CDSCO from India, are fully supportive and appreciative of any automation and digitization. However, they expect proper qualifications and CSV activities to ensure that the systems have all necessary controls against manipulation or deletion.

In the case of AI, these agencies are a bit more cautious. While the FDA acknowledges that 40% of the submissions now include AI-predicted documentation. They introduced two guidelines in January 2025—one on AI-enabled medical devices and the other on AI for regulatory decision-making for drug and biological products. These documents are open for comments and suggestions.

Challenges posed by AI – While AI is a very productive tool, it also poses challenges to the agency and the industry, such as ethical and security considerations like improper data sharing and cybersecurity risks. Algorithms with high degrees of opacity or those whose internal operations are not visible can amplify errors and pre-existing biases in data.

8. The Future of Pharma: From Reactive to Predictive

Pharma is always moving towards robust systems and processes with a focus on timely supplies and patient safety. Automation brings that comfort. Moving from reactive QA to predictive quality systems avoids failures and waste in the system.

Automation and digitization have provided that advantage, and batches manufactured with this support have always helped bring predictive and desired quality in various areas of work—from R&D to production to logistics.

9. Conclusion: Digitization as a Cultural Transformation

Digitization and automation with artificial intelligence are making modern pharma operations more reliable. What used to take months together to derive a decision is now done in a few seconds. That’s happening because of digitization, analysis, and deriving the further course of action.

When digitization is implemented, the human errors of the “jugaad” attitude are slowly vanishing. The system provides a more confident solution than what executives may take from their experience.

The success of digitization is not in the tool—but in how it’s used. The same tools are used differently by different companies. That depends on the enthusiasm of people to utilize the new tool in a better way. But the pharma society has not changed much. There are pressures and skeptical personalities who do not progress as quickly as in other industries. This is further affected by some managements looking for low-cost solutions. For example: “I want digitization at low cost.” That would only mean an Excel sheet. When you add algorithms, naturally, the cost of the system increases.

Global players are eager to test new tools and get the best out of them. It could be due to manpower shortages that lead to automation and digitization in Western countries. In contrast, the availability of large manpower in India is the reason for slower digitization. As discussed earlier, the workforce is available but lacks the required skills.

There’s a meme in India – Management will spend when there is a regulatory observation. Does this mean we are waiting for regulatory observations? Are we not looking for visibility in the system that provides no surprises—that’s Predictive Quality.

Going global also needs global thinking and global actions. Those who don’t want to take that risk and want to manage with a low-cost approach will also live with a low-profit approach, as it would mean low innovation. The choice is up to the industry and its leaders.

 Is this not food for thought?