Pioneers in Bioprocessing: Q&A with Biopharma Executive, Steven Lang, Ph.D.

Invert is back with another installment of our Q&A series, Pioneers In Bioprocessing, where we chat with experts in biomanufacturing and biotechnology to discuss their work.

This time, Invert spoke with Steven Lang, Ph.D., MBA, a pharmaceutical and food tech executive with over 20 years of leadership in large biopharma corporations, small contract research organizations, and startups, including time spent working on biologic drugs at Johnson & Johnson and Genentech. Most recently, Steven served as VP of Bioprocess Development at Upside Foods, a food tech company that became the first-ever cell-cultivated meat company to sell its product in America. Steven’s expertise spans strategic planning, bioprocess improvement, and CMC activities from cell line development to regulatory filing. He has led a number of efforts to transition biologics from discovery through development, paying special attention to increasing throughput and sourcing efficiencies through workflow digitization and bioprocess data analytics.

Note: this interview was edited for length and clarity.

To start us off, tell us how you got into bioprocessing.

My first job was as a postdoc within J&J. That gave me great exposure to small molecule discovery and a really great introduction to industrial science. From there, I landed a job within J&J as a cell line developer and what was the flagship organization for biologics within J&J, called Centocor.

In those early days of biologics, we were establishing a lot of critical technology as well as exploring countless new avenues. It was a really exciting time, even though we didn’t realize how big of an impact biologics were going to have.

What do you see as your greatest success so far?

One of the things that I think I am most proud of is the collaboration we had with Genmab back at J&J when we in-licensed Daratumumab as well as the Duobody technology. Because we had built out a great due diligence and developability package within J&J, we were able to uncover liabilities early on and then mitigate them very rapidly in both upstream and downstream processing. Ultimately, this helped get these bispecifics into the clinic as quickly as possible.

From your experience, what would you say are the main obstacles to transitioning biologics from discovery through development?

I would say balancing risk and speed is really the biggest challenge, and it has been a consistent theme over the last ten to fifteen years. As biologics become more competitive, getting to the market first is paramount. Especially for newer modalities like gene and cell therapies, being a first mover is really important.

I learned very early in my career that it’s a challenge to move science at the pace that business needs it to. Having the right data in place is paramount to being able to balance business demands with the scientific challenges of moving at a very fast pace, while still delivering a safe and efficacious product at the end.

What can companies do to increase the likelihood of success during cell line and bioprocess development?

The one that I always lean back on is to delay major decisions. While you need to keep progress moving rapidly, kick the can down the road as long as you can before locking your molecule sequence or process. But, doing that very effectively requires parallel processing.

With the automation and data systems of today, it’s not that challenging or expensive to do parallel processing and run multiple molecules, or a panel of molecules, that may have different mechanisms of action and attributes in their design. Keep those in play as long as possible before you start generating your GLP tox data or your GMP material. That allows you to see if one will outperform others in later stage in vitro or in vivo studies and provide a better competitive edge.

How does bioprocess data management play into commercial efforts? Why is it important?

We always have to remember that the data and the information that our scientists and engineers generate are the most valuable things that we can produce.

I’ve been in both new and mature businesses where bioprocess data has been an afterthought and not valued as it should. Instead, we’ve got to think about this data as a precursor to the knowledge that’s going to really make us successful.

The hodgepodge that we’ve stitched together to just get to our bioprocess data and make it accessible is a huge disservice to the science and innovation that we’re trying to execute.

But, I think we’re now getting to the right end of it. We’re seeing the value that biomanufacturing can bring, and by capturing all of that bioprocessing data in an appropriate place that’s accessible to the people who are actually developing the processes, we can make huge advances.

That’s where digital transformation and technologies are just so important. I would say so much information is being lost between the cracks just because we don’t have good integrated systems to capture everything. If we provide that data to bioengineers, they can build better processes.

Are you surprised that the application of digital technologies in bioprocessing and biomanufacturing at biopharma companies hasn’t received as much attention as the discovery side?

I am a little bit surprised because we generate so much data. Once you get down to a commercial process, you’re running the same thing over and over again. That is just fertile ground for machine learning and artificial intelligence. But, you have to be able to grab all that data and get it to a place where AI and ML can actually work on it.

I think the problem is that we’ve really kind of thought of biomanufacturing as just an operation rather than a source of new information. As we develop these bioprocesses and get them into different phases and different scales, we can learn so much, but there’s still data and information that we’re not using effectively or completely missing.

I think the problem is that we’ve really kind of thought of biomanufacturing as just an operation rather than a source of new information…We need to be able to capture all that info one way or the other. And, it’s either going to be captured in a bioengineer’s head or as institutional knowledge for the business.

We need to be able to capture all that info one way or the other. And, it’s either going to be captured in a bioengineer’s head or as institutional knowledge for the business. Naturally, it’s much more valuable as institutional knowledge that can be shared and reused for future projects. Whereas, an individual’s knowledge is not very useful unless it is shared and codified in institutional knowledge. Today’s digital technologies can facilitate both individual and institutional learning.

What roles do you think digital technologies can play in successful bioprocess development efforts in the future?

If you’re launching a commercial process, so much effort is focused on the verification runs for both food and biopharmaceuticals. But imagine a world where you could easily aggregate all of the data you’ve collected from the early stages of product and process development when you are trying to understand your biologic’s expression, potential liabilities, post-translational modifications, and how the process affects them. You could then wrap all of that data up neatly into your package.

In addition to your verification runs, you’d be able to show that there’s a huge depth of data demonstrating that the process is robust and controllable throughout various scales.

As another example, I think using digital tools to institutionalize high-content data, like genomics or mass spec, is really critical for biomanufacturing. There’s so much data there you can revisit. But, how do you parse it? How do you make it useful? That type of automation is really going to be valuable for us going forward.

Reflecting on your work on bispecifics and cultured meat, how do bioprocess development and CMC activities differ for newer modalities and product types compared to more established ones?

It requires a lot more data generation and analytics. As you’re thinking about a new pharma product, you want to be able to understand both the known liabilities as well as the unknown liabilities. The same is true in the food space. As you go into a new food, you’ll have to have different compositions, different allergy concerns, et cetera.

What insight did you gain from working at a contract research company that changed your perspectives when it comes to hiring and working with CROs, CDMOs, and CMOs?

Working on the other side of the desk, if you will, in a service organization and providing service gave me a great perspective on how better to do it in the future. When you’re thinking of externalizing or outsourcing R&D work, you really need to think of it as an external workbench. So, make sure that you have a great fit between the project’s technical needs and the capabilities of the CROs.

Perhaps most importantly, you must build productive relationships with your contract partners to not only capitalize on their expertise but also understand their work and how it gets done in their labs. That helps you not only deliver on the technology but also communicate and really interrogate the data as much as possible. That kind of collaboration can lead to valuable serendipitous findings along the way.

After working for years in biopharma, what brought you to work on cultured meat at Upside Foods?

I think it’s a fascinating field, to be really honest. Everyone knows it is extremely expensive to produce a commodity product such as food using biotechnology, and cultured meat still requires some major innovations. But having watched huge advances in biotechnology for the last 20 years, the trajectory is very promising. It was really that trajectory of success that I think drew me to use biotechnology for food.

To my knowledge, reaching a 50,000 to 100,000-liter bioreactor scale has not been done successfully for animal cell culture, but that’s part of the aim of cultured meat. The need to reduce the cost of goods sold (COGS) down to pennies on the pound is mind-blowing. But being a part of the innovation required to get to that stage is a lot of fun.

In addition to the thrill of working on solving that technical challenge, I was also motivated to work with great colleagues and peers. I had previously worked with a number of folks at Genentech who are now in the food industry. Knowing that respected experts have made that jump already kind of opened my eyes to the potential of food.

How are bioprocess development and biomanufacturing different between biopharmaceutical and food products?

The processes that we are using for generating food products are largely the same as what we’re using for biopharmaceuticals. It’s the inputs and the outputs that are different. In biopharmaceuticals, we’ve been using the same cell lines for numerous years. We have a wealth of knowledge about how those cell lines behave, and we can apply that knowledge to the next project coming along.

In the food space, we’re going to have a lot of different inputs from different cell substrates, species, and cell types. Each one of those cell types may require bespoke media and process development, which will take time.

On the outputs side, the quality systems and regulatory requirements are different. And then, ultimately, because of the COGS demands and distribution mechanisms for a food product, your supply chain is going to be quite distinct as well.

In your opinion, what are the most exciting things happening in biomanufacturing, biotech, and biopharma right now?

Renewed focus on bioprocess data. Getting data into the hands of people developing the processes has been a blind spot for the industry for many years. So, I’m really glad that we’re seeing some attention brought to maturing data systems, and companies like Invert are helping us pull all this data together.

Getting data into the hands of people developing the processes has been a blind spot for the industry for many years. So, I’m really glad that we’re seeing some attention brought to maturing data systems, and companies like Invert are helping us pull all this data together.

I also find the focus on using biotech for environmental causes is really invigorating. I just love to see people at conferences talking about sustainability and using biotechnology in other fields that maybe would’ve been prohibitive previously. The food industry is one of them.

What are your thoughts on the application of AI and ML in bioprocess development and commercial biomanufacturing?

AI certainly can change a lot of what we do if we can get the data in the right place.

There are great opportunities for AI and ML to look at all of the data that we generate from R&D all the way out to commercial, and help us notice things that we’ve not paid attention to before. Could it be bioreactor diameter versus sparging? There may be an important connection there that we’ve just never explored that AI/ML can uncover.

Ultimately, these types of automated data systems will take some of the routine activities out of biopharmaceuticals. Analyzing images, studying clonality, and looking for particles in vials, are all things that we can train AI to do.

How do you think we can best grow the bioeconomy as a community? What improvements and solutions do bioprocessing and biomanufacturing still need?

I think what we need to do is, of course, get more people into this field. I’m really looking towards government support of institutions to specialize in biomanufacturing.

On a more tactical level, I really want companies to recognize the value of the data and build those systems early so that we’re not constantly fighting with IT and bolting on solutions that are just going to cost us money and slow us down. Taking that holistic data approach from the very beginning is really critical for our ongoing success.

What are the most valuable lessons you’ve learned in your career?

The one that I always think about comes from early on in my career as a postdoc. I realized that most investigators are not good managers or leaders because they’re trained as scientists, where they’ve had to really put their heads down and solely focus on a technical field.

Working on my MBA was an eye-opener for me because it helped me better understand leadership, mentoring, and organizational dynamics. All of which, we require in scientific endeavors, even though they are not usually taught to scientific leaders.

I firmly believe that prioritizing the well-being and professional development of our scientists and engineers leads to a more innovative and successful organization. When we invest in our people, we empower them to deliver exceptional work. The products will come later if you focus on the people first.

I firmly believe that prioritizing the well-being and professional development of our scientists and engineers leads to a more innovative and successful organization. When we invest in our people, we empower them to deliver exceptional work. The products will come later if you focus on the people first.

What advice do you have for others aiming to make bioproducts?

When I mentor others, I talk to them early on about the value of having technical depth. We are in a very technical, scientific-focused arena, and that is table stakes. So, having some depth of knowledge in a very specific field or specialization is critical.

But from there, you need to branch out. I encourage people to join cross-functional teams and get their voices heard. Always think of everyone around you as somebody to learn from.

When you’re not working on bioprocesses, what do you like to do with your free time?

I’ve taken up cycling, so I try to do that every day. And then the other thing I’ve been doing, much to my wife’s chagrin, is renovating our house. There’s very little you cannot do with the right tool and YouTube!

Huge thank you to Steven for chatting with us and sharing his thoughts. Thanks for reading, and stay tuned for the next edition!