digitalisation in the pharmaceutical industry no deviation

Digitalization in the pharmaceutical industry

Last year during the ISPE Singapore conference 2020, I was fortunate to moderate a discussion on Reaching Digital Maturity Through Pharma 4.0. I shared the panel with Roger Harty, Director of EMEA & APAC, Belgium, Samme Wang, Head of Engineering and Technology Asia, Bayer, Singapore, Rajnish Narula, Director Business Excellence, Pfizer, Singapore, Jennie Burton, Operations Digital Transformation Lead, AstraZeneca, Australia, and James Wu, Chief IT Officer, Roche, Taiwan. Since then, the digitalization projects have kept coming to us, and while some failed and some succeeded, we want to share what we’ve learned. 

For example, at the moment, No deviation is working to understand the benefits of applying digital twins for chiller and energy optimisation in collaboration with NTU and other major pharmaceutical MNCs in Singapore. We are also helping the worldwide implementation of a paperless CQV solution on multiple sites. We have been working on warehouse optimisation through data visualisation as well as discussing software upgrading and data migrations. 

While the reborn ISPE Singapore conference is coming up fast, I thought it would be time to listen to the panellist’s advice and see how they were relevant, to succeed in those projects.

First, what is digitalization? 

As stated by Wikipedia, digitalization is the conversion of text, pictures, or sound into a digital form that can be processed by a computer.

The good news is that we already perform digitalization, or are using it daily (every time you send an e-mail or post a picture on social media). But then, why the big fuss?

The promise is that digitalization will improve our quality system and reduce the cost of goods while making people on the shop floor happier, by having computers solving complex problems and helping to make complex decisions faster.digitalisation 1 no deviation

For example, a computer can process much more data than the human brain. The benefit of digitalization is the capability of processing data to drive our decision. 

As humans, we can only process data that are 2 dimensional (graph/drawing); sometimes, we can process data in 3 dimensions. Aside from the apparent 3D world we live in, most of us, if not trained, will not compute a 3D plot easily. Computers, on the other hand, have virtually no limit to the number of dimensions they can process. The use of digitalization that transforms everything into numbers will allow matrix computation. (Please refer to the picture)

Those computation types will allow Principal Component Analysis to shrink a multidimensional space into a 2D plot (trends or dashboard), enabling humans to make decisions in accepting or rejecting a complex process outcome.  

This is what you can hope for in a process with a well-defined design space where the relationship between parameters is known. A simple trend can represent the state of control, and if the trend deviates from this state, you can dig out which of the PCA parameters is losing it.

Digitalization is a buzzword and you will face many challenges. So let’s take a simple example of a challenge you might face.

Your boss asks you to identify which part of the facade is always in the sun. You decide to take a snapshot of your workplace building. Congratulations!! You have created your first digital twin, but will it help you solve your problem? You quickly realise that you are missing a lot of information in your digital twin to actually be capable of making decisions. 

  • If your picture is black and white and overexposed, you will want to have a better data acquisition system. 
  • Maybe the angle of the building does not show what you are looking for. 

How will you process that data to make a decision and which software will you use to highlight the critical parameters needed to make that decision?

You then go to your boss to get an Adobe Photoshop license, but he is telling you IT does not allow the use of external software, and the company has an agreement with Affinity Photo; the problem is you never use that software.

You decide you require more pictures and from different angles and timing to allow a decision. So you give a digital camera to the 1000 employees in the company and ask them to take multiple photos of the building. But,

  • the names used to save the files are not consistent; 
  • they do not save the picture in the same resolution; 
  • some have randomly put their holiday picture in the folder. 

Now, you have way too much information available, but none to help you make the decision you wish. Worse, you realise that some people didn’t want to use the camera at all and preferred to sketch on paper…

In most digitisation projects, you will encounter similar problems to those outlined in the example above. 

How to avoid this, what should you do?

  1. Make a strategic analysis and set up a target. This will generally formalise in the shape of a project charter.
  2. Assess your digital maturity and the available resources in both the domain of expertise you want to apply your digitalization (i.e energy saving, process optimisation…) and the digital field (IT, programmer, geek, hackers…).
  3. Make a plan and start implementing.

You can see it is just No deviation’s concept of ‘Understand, Observe, Define, Implement’ that is now applied to a new domain. 

It is essential to run a proof of concept before going big and be ready to pull the plug if needed. Also, digitalization is a growth process and so, it is important to record the lessons learned. You will need them in the future (there is no way forward without digitalization), adopt these lessons and improve  (also called PDCA) as you further increase your digital maturity.

One way to reduce the effort for your organisation is to make sure the effort is scalable; this will allow you to achieve an economy of scale and skills. I, therefore, invite you also to read our blog on the importance of governance.

And yes, data integrity is vital in pharma. It is everything in digitalization. If you can’t trust your data, then how will you trust the decision made? To know more about data integrity, read here.

If you have any questions or would like our help in better understanding the need for digitalization in the pharmaceutical industry, please do contact us for a discussion at

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