SAS´ EMEA Sales Director for the Life Sciences, Jonathan Riches, sees a lot of opportunities for SAS to further solidify its footprint in R&D and extend SAS capabilities into new functions. I talked to him just a few weeks after he started in his new role on Jan. 1 to get his view on the future.
Jonathan, you are taking over the lead for this industry in a moment of peak expectations for pharmaceutical companies.
That’s right – in the mainstream media since COVID-19, now everyone knows the names of big pharma giants like AstraZeneca, Pfizer, Bayer. The last 12 months have proven the important contribution of important pharmaceutical manufacturers to the wider world. COVID has also brought to the surface the tectonic shifts in this industry over the last 10 years. It’s not just about bigger pharma companies but also how the smaller biotech companies like BioNTech, Moderna or Curavec deliver innovation.
When these companies come together to collaborate, we see how innovation and scale for regulatory submissions can happen and help bring drugs to market. SAS continues to help all actors in the life sciences ecosystem to glean insights out of digital information. It is exciting to be part of the action and there is a lot more in store to show that SAS analytics really makes organisations more effective.
SAS has a long tradition in drug development. Why? And will this continue in the future, as well?
Traditionally, SAS has helped pharmaceutical companies to manage and analyze clinical trial data since the company started in 1976. Mark Lambrecht, our Global Practice Lead at SAS, reminded us of that in your recent interview. And I share his thoughts: We will continue to invest in software solutions around drug development to make it better, easier and faster. Drug development relies on statistically robust data and results – and SAS has an unmatched experience in this field. We support the life sciences industry every day.
In addition to developing and helping drugs seek regulatory approval, we have also seen recently other challenges further down the supply chains: how to secure, scale and stabilize a reliable production? How to automatically monitor the production quality, the supply chain and even the potency of drugs? These are some of the questions my team and I have discussed with our customers on a regular basis these days.
Why is SAS in a position to help here? At the end of the day, we are a software company for analytics software. Can you explain this a little bit?
I would love to! The beauty of SAS is that we have solutions and use cases across many sectors. We own a treasure of experience from other industries that we can bring to life science. For example, in retail and CPG most major players use SAS day-in and day-out to help understand demand by forecasting using both demand history and downstream consumer data. In the short time I have been in my new role, I have seen the same issues with big pharma. Most supply chain heads just buffer up their inventory to help cover shortages, and this is mostly based on gut feel. Nonetheless, they have the data available to help make the planning more agile and therefore reduce inventory costs. For sure, it is complex, it requires domain knowledge – but if it was easy, everyone could support it.
We are also observing life science organisations tackle other use cases using SAS as part of their digital transformation. One large UK-headquartered pharma has invested in a more efficient way to secure production quality. Others are laser-focused on efficiency and have invested in methods such as real-world evidence, monitoring effects and adverse effects in an automated way. The mandate I have given my team this year is to go out and share the best practices on how our technology is being used across the value chains.
But allow me to ask: At the end of the day the big companies are competitors – now even challenged by smaller biotechs. Why should they all use the same tools?
The main differentiator in this industry, just like in others, is constant innovation. This depends on the brilliant ideas of highly skilled scientists. This is nothing you can replace with any kind of tools. Think about paper and a pen: Everyone has the same tools – but only a few people can write novels with that. We at SAS deliver everything in the analytical space. And our customers create their own stories with our help. Also, every therapeutic development process is unique. And the ability to understand and make processes more efficient is in the DNA of SAS.
What is the next big thing from your perspective for life sciences organisations?
That is certainly the ability to run software and bring all information to the cloud – and collaboration in the cloud. As a result, pharmaceutical companies will become producers of both medicines and digital health therapies over time. We already touched upon the fact that biotechs and established firms are starting to collaborate more intensively than before. We at SAS create the space for that, and we have brought our analytical technology to run it in cloud-based deployments. The newest release of our core technology was built cloud-native – and more open than ever before. Diverse teams of Python, R or SAS coders now really can interact on a programmatic level in a common and governed environment. Just a few hints: A joint ModelOps framework will allow bringing new ideas much faster to market than ever before.
On a personal note: You are covering now a very vibrant industry with some of our key clients’ headquarters based in Europe – with strong subsidiaries across the globe. Normally you would travel a lot, wouldn´t you?
Just like everyone on the front line at SAS, we are passionate about spending time directly with our customers. It is so important for building trustful relationships. I still hope the new normal will mean that we get to sit down and spend time with our clients physically instead of a screen. I personally cannot wait to get out on the road. In the meantime, my wife is happy that I am around at home to help out more.
We at SAS create the space for that, and we have brought our analytical technology to run it in cloud-based deployments. The newest release of our core technology was built cloud-native – and more open than ever before. Diverse teams of Python, R or SAS coders now really can interact on a programmatic level in a common and governed environment.