Peter please can you tell us about all the work Medicines Discovery Catapult has been doing over the last couple of years?
My story begins back in March 2020 when it was recognized that, in the UK, we did not have the testing infrastructure that was going to be needed as the true scale of the pandemic began to emerge.
I got asked to help set something up. There were no buildings, laboratories, automation, assay equipment, or people. It was a case of begging, borrowing, and bartering for everything because in the early days of this pandemic you could not suddenly find hundreds of scientists, dozens of tissue culture hoods, a whole load of liquid handling systems, et cetera. We had to find ways to make that happen.
We had fantastic engagement from our sector - volunteers from 15 different businesses dropped what they were doing and came to work in the facility. We found a hotel that was still open at Manchester Airport and put up several hundred scientists in that hotel, operating a shuttle bus from hotel to site. We got some architects and builders in, a whole load of equipment, help to move in from the army, assistance from universities around the UK, and an assay in place. Within 16 days we were testing clinical samples for the UK.
The scale of the collaboration endeavor was unlike anything I have ever seen before and hopefully unlike anything I will ever be involved in leading again. Medicines Discovery Catapult was at the heart of it. We had fantastic help from Alderley Park, landlords, companies like AstraZeneca, and universities such as Manchester and Leeds.
There are too many people I could thank for making it happen. I think everybody recognized, as scientists, that doing some science to help the pandemic was better than sitting at home worrying about the pandemic. There was a real mobilization at our site, the UK and internationally, of scientists who could help. We had senior professors back in tissue culture hoods prepping samples into vials because they wanted to help.
It was heartwarming to see how much this industry pulled together. From diagnostic suppliers to automation specialists, to pharma companies, to not for profits, to universities, all were doing what they could do to help. We coordinated the efforts at Alderley Park, as one of three national labs. While I am no longer directly involved, that lab is continuing and has now done more than 20 million samples and employed 700 people at any one time. Well over a thousand staff have been trained in how to do diagnostic testing. Hopefully, that is something that has helped the UK and can leave a fantastic legacy for the future.
Michael, can you share with us Hamilton's story during the pandemic, and looking forward?
Like all of us in March 2022, the world came roaring at us. We are a supplier of sample preparation, sample processing, and sample access technologies that include storage systems, labware, and processing equipment, at temperatures from ambient down to -80 degrees celsius. We are deployed at academic institutions, research hospitals, and large pharma around the world.
As March hit us, we were impacted by protecting our employees, moving remotely to work offsite, and the challenge of supporting and deploying critical equipment in the COVID research pipeline. Each day was an interesting, unexplored avenue for all of us.
Our equipment, based on where it sits in R&D organizations, was critical to keep working and our employees needed to be there. From our field service engineers to our sales folks, everyone needed to figure out ways to do that. Many of us worked from our home offices, but many of us could not. Our production facilities continued to work. We were open every day of the week since March 2020 and had to figure out how to do that.
On top of that, we were also in the supply chain, and much of our equipment and technologies were needed by new labs. We had to manage and allocate products and resources carefully.
We had much more demand than supply. We wake up every day trying to help the world, our families, and our friends be healthy, live longer, and survive things like the pandemic. Thank goodness we have that in our hearts and souls and we work to do that.
Collaborations came at us quickly. For example, there is one we are doing now with a startup at Harvard and their partner Rhinostics, a company here in Wayland, Massachusetts, that created some alternative swab testing hardware. This was deployed in very high volumes because testing demand went up. We have robots and automation that can make this stuff work in high throughput labs.
They came to us with the challenge to remove the tops of test tubes. We got together with LabElite DeCapper technologies and created an automation that allows caps to be capped and decapped in a very, very high throughput manner. That relationship continues.
The pandemic continues to take turns left and right. Even as the throughput needs are diminishing and we make progress on the virus, we are challenged with other cases. Our storage products, where we store research samples at up to -80, continue to be in demand.
There are lots of large repositories and organizations filling and building facilities to house R&D samples. We are a global supplier with facilities in Switzerland, Tokyo, and Australia, with days of more than eight to five across weekends in different time zones around the world. I think we are looking forward to a little calming in the market and some shorter days.
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Simon, can you tell us what you were doing when the pandemic began? And how did your work, or even life projects, change?
I was working for Waters Corporation when the pandemic came out, responsible for software engineering with 450 employees spread across three continents and five different countries. First off, we needed to protect those employees and we were quite fortunate in that respect in the software team at Waters.
We had invested quite dramatically in new, state-of-the-art development tools for our software teams in the previous couple of years, which was lucky, to be honest. Within the course of a week, we were able to get all 450 employees to home offices to keep productivity going. In fact, during my tenure at Waters, we actually increased productivity during that first year and a half of the pandemic. However, it was perhaps not completely sustainable because the effort everyone was putting in was 120%.
Once we had made our employees safe, we started to think about the business and how we could get business continuity to keep procurement for our customers moving and to keep critical technologies moving. After we had executed that, we started to think about, "Okay, what does this mean? How do we plan ahead to start making life better and more effective for our customers?" What became abundantly clear was that unlike the software engineering kind of world that I just talked about, our customers still had to send their scientists into the labs.
The highest value asset that a pharma company has in their portfolio are the people that do the science. It turned out that those scientists were being forced to go into the laboratory still because a lot of the existing technologies in the labs could not be run remotely. It was still workstation-based or enterprise class-based, with very little cloud-based technology in the laboratory, unlike the software industry which could pivot because everything was running in the cloud.
This concept of a lights-out laboratory came to the forefront of our customer’s minds. How could the industry start to enable a lab that did not need a person per instrument feeding samples, analyzing the data, reviewing the data, collaborating on the data, in front of a whiteboard? It was quite shocking to some extent, speaking to those customers about what they do in the lab. In some cases, they were putting sticky notes on the front of instruments to schedule what experiments would need to be done.
At a personal level, that led me to question whether I was placed professionally to right this within the pharma industry. It was at that point that I decided to jump across to TetraScience. TetraScience is a cloud-first company working on the digitalization of laboratories, removing those data silos to allow data to be liquid across the laboratory.
The entire industry was already re-platforming. At the beginning of COVID, Tetra had about 20 employees. When I joined about seven months ago, we had about 50 employees, and now we have about 160 employees.
I think the reasons for that are clear. I remember speaking to a top 10 pharma company in the midst of the first three months of the pandemic, and I will never forget the words they said. "We had a plan for digital transformation that was going to ride over the next five years. We are now compressing that plan into the 18 next months." I think that is now the way that TetraScience is riding, and we are seeing this increasing need to make data available for anyone and to create an open ecosystem that crosses the vendor divides.
Why is that important? At the simplest level, the pharma industry has been sped up and companies want to be able to look at what is happening in manufacturing. Say you have a presented yield difference in manufacturing. They want to be able to search that molecule and search all of the analytical technologies that analyze that molecule during early research discovery, and process scale-up.
Today, you cannot actually do that, because the data is in silos both within the pharma value chain and within each analytical technology. It becomes clear that the wave of digital transformation and automation required to get this lights-out laboratory is now going to be the primary post-pandemic focus for the entire biotech and pharma industry.
The COVID-19 pandemic has highlighted the importance of collaboration on a global scale. Are you hopeful that this level of collaboration will continue after the pandemic? How are your respective companies trying to promote collaboration?
Peter: I have been a massive advocate for companies working together for a decade or more. I think often what they get stuck on is contracts, who owns what, and what if that guy does not do their bit? I remember going to one negotiation when I was in the pharma world, and the other pharma company turned up with seven lawyers it had flown in from America. They wanted to know whom to sue when things went wrong, to protect themselves.
When you just want to get stuff done, you do not have the time for that, and I think what we saw here is that sense that actually we do not have to do that, particularly when people trust each other and are trying to see the bigger picture. It is not always about who gets sued when things go wrong. It is not even always about who gets to sell the product at the end. One of the things I have always said in my career is that we are all patients as well as scientists, and we all know patients as well as scientists.
So, if that other guy makes a drug that cures cancer, that is great. It does not have to be me that makes the money, because I might be the person who needs the medicine. I think the philosophy of coming into science to do something good for people is probably back at the forefront of people's minds now. I hope that philosophy sticks with us.
Simon: Even before the pandemic, I think an average of seven companies would collaborate on any new molecule. I think we are only going to see more of that as contract research and contract development organizations participate in new modalities.
I think another thing that has also come out of the pandemic is that collaboration is not just for the pharma companies, but the vendors that serve the pharma companies. Today, at TetraScience, we are seeing this drive to create an open ecosystem where data is independent because the data is not owned by any particular company and it is ultimately owned by the patient, which is what that data is for.
Today, all that data tends to be in different formats that are undecipherable between different technologies used by different parts within a pharma company, and then different companies. This is why the digital transformation aspect of what is happening within lab automation is so important. We call it data liquidity. If you think about a JPEG picture today, you can look at that picture on any device, and you can take a picture on any device. You cannot actually do that with scientific data, which is arguably humankind's most valuable asset as we are challenged with more episodes like the COVID pandemic.
Michael: We invest a good amount of money in new product development at the Hamilton Company. Some of the development of new products is done through collaborations or organically done through our own R&D. The collaboration with Rhinostics and Harvard was good in the sense that we trusted each other. None of us knew where it was going or what the COVID path was going to be. In the end, we came up with something quite fruitful which is now out in the market helping patients.
The roadmap on collaboration is never really clear, in my experience. It takes a good amount of trust from the collaborators. They are not always fruitful, but it sure does feel good when they are, and we are always looking for more of those.
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What is your current assessment of the biotech and scientific community's approach and progress two years into the pandemic?
Michael: I think it has been quite good from where I sit as a patient. I am proud of the advancement in the vaccine. Nothing else has been ever done that fast in the history of mankind, and I am proud to be part of it.
Peter: Medicines Discovery Catapult works with the smaller companies, the biotechs, and the SMES, and I think we have seen a real focus around future vaccine technologies, drug delivery technologies, and planning for the future.
The things that have been delivered with existing technologies, or nearly existing technologies, have been amazing, and the speed of getting these vaccines through has been beyond what the industry probably felt it was able to do. I think it is fantastic to see the logistical capabilities of companies, and organizations working together.
I am also delighted to see the boost this has given to the next generation of drug and vaccine delivery technologies. People have seen what has been possible with lipid nanoparticles and they are now looking at a whole range of additional delivery approaches. I think that broadens out the future because it is great that we now have more tools in the toolbox.
We are in a pretty amazing place, two years into a pandemic. But we also all recognize this is not, sadly, the last pandemic of our lifetime, and that it is really important that we continue to support the next wave of innovators so that for whatever comes at us next time, we have got more tools to combat it.
Simon: I think one of the most eyeopening things has not just been the emergence of new tool providers and new biotech players, but the excitement of a new generation of scientists. I think this has shone a light on science, particularly life sciences. It has become instantly recognizable as a career to work in and make an impact, which I think had become diluted with the emergence of the tech industries over the last kind of 10, or 20 years.
To be a graduate in biology, biochemistry or biophysics is exciting, cool, hip, and trendy again, which I think can only accelerate the development of new modalities for all sorts of disease states.
Recent advancements in machine learning and AI is helping to tackle volumes of research data, but what more needs to be done? Are there any limitations when adopting AI for data analysis?
(Simon): The advancements in AI, certainly in life sciences, are currently limited entirely by the ability to get the data in a usable form. You need to first harmonize the data and make it follow some kind of pattern that you can recognize. The most simple, basic terms like the date and time format are different depending on the type of software and hardware that produces that data.
To be able to do anything you need to transform the data into a machine-readable form that is understandable. That is probably the biggest lift that the industry is undergoing at the moment, and some multiple projects and companies are trying to focus on preparing the data for AI. The example I gave before of just being able to search your data at Novo Nordisk gives an indication of the infancy of preparing data for AI. If you cannot actually search the sample name or the molecule type, then it is unclear how you can do advanced machine learning and AI.
Fortunately, our company, and other companies, are really focused on making that data available right now. We are engaged with all of the top 10 pharma companies, as well as tens of biotech companies, trying to prepare that data for advanced data science.
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What are the byproducts or legacies of the pandemic for the biotech and scientific communities? Are you willing to make any predictions of what those legacies might bring?
(Peter): A better understanding of the importance of diagnostics. In the drug discovery industry, people get very excited about a new medicine and typically not very excited about a new diagnostics. Historically, it has been Cinderella science. What we have seen is not just scientists, but now the entire population understanding diagnostic tests, having detailed opinions on the benefits of a PCR assay over a lateral flow test, and being willing to do diagnostics across a range of situations, in their home or their workplace.
That is not limited to importance within a pandemic. If we could get the population to be willing to engage with diagnostics, take it seriously and understand its nuances in community diagnostic hubs, hospitals, and at home, there are a whole range of industry opportunities that open up. If we can get governments to be willing to invest and support the diagnostics innovation industry, there are a whole raft of opportunities in innovative diagnostic tests and sophisticated data analysis of population changes.
(Michael): Due to the pandemic, all of us are more connected with pharma and biotech in the sense of the impact that they have played with the vaccine and other therapies. I think we are all more aware of taking medicine, pills, or getting vaccines. The pharma and biotech industries have come front and center to us. Even just the names of these pharma companies that have been in the play are much more familiar to my children, my wife, and my friends now.
(Simon): I think the public’s expectations from the industry have changed now. Everyone expects us to be able to run faster and safer and that those trends are going to continue. But it is going to be a challenge to manage these expectations. A new molecule for every disease state cannot be developed in 40 days, or 100 days. The industry cannot cure cancer at the same speed as we were able to take an RNA platform and adapt it for COVID.
Another prediction is that I expect we will start to see more and more digital-first organizations in contract manufacturing. A few have come to the fore that are scaling themselves as completely digital organizations, designed to be able to take a modality and get it to market in days, rather than years.
The speed within the wider industry is re-normalizing big pharma, and will then enable the biotech industry, which has very novel ideas but has not necessarily been able to get the scale they need, to bring the product to market as quickly as they would expect. Now, with the investment in contract manufacturing, I think there is going to be a heightened sense of expectation that any new molecule, once proven safe, can be consumed by patients within six months.
With rapid advancements in all areas of life sciences due to the COVID-19 pandemic, what are you personally most looking forward to in the next 10 years within the life sciences industry?
(Michael): Being an R&D-focused professional, I am looking forward to the spark in that area of pharma and biotech continuing. I think it came along at a good time for us drug discovery folk. If you look back 20 years, high and ultra-high-throughput screening took the industry by storm and we got the most out of that. One of the silver linings from the COVID outbreak is that that spark has been ignited again, allowing us to take more risks and have more successes.
(Simon): The focus on science has been fantastic. I have spent a lot of my personal career on the manufacturing side of pharmaceuticals and running the safer side of things. I think the technology gains that we have seen in research and development have been incredible: scaling-up manufacturing to make it faster and safer and being able to look across data sites with advanced machine learning and AI.
We are reimagining the scientific manufacturing space, moving to a space that is like financial services where you never have to check your credit card statement anymore because your bank will come and tell you if there has been a false transaction on it. To be able to do similar things across the pharma value chain, to look for patterns of where there might be a problem, indicate it, and solve it before any therapy ever gets to patients is the bit that I am most personally excited for, as I spent 20 years of my career working in the compliant end of the pharma value chain.
(Peter): In the Lighthouse Lab we set up, we had kids from 17, fresh graduates, and fresh PhDs thrust into the heart of the industrial setting very early in their career, taking on incredible levels of responsibilities and showing their efforts and capabilities. I am really looking forward to seeing those people coming through the industry into leadership positions because we were able to identify some fantastic young people and give them real opportunities to get started in the industry. I am sure many of them will go on to thrive.
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