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COVID-19 and the life sciences; What have we discovered?

My story begins again in March 2020 when it was acknowledged that, within the UK, we didn’t have the testing infrastructure that was going to be wanted because the true scale of the pandemic started to emerge.

I obtained requested to assist set one thing up. There have been no buildings, laboratories, automation, assay tools, or folks. It was a case of begging, borrowing, and bartering for all the pieces as a result of within the early days of this pandemic you could possibly not abruptly discover a whole bunch of scientists, dozens of tissue tradition hoods, an entire load of liquid dealing with programs, et cetera. We needed to discover methods to make that occur.

We had unbelievable engagement from our sector – volunteers from 15 totally different companies dropped what they have been doing and got here to work within the facility. We discovered a resort that was nonetheless open at Manchester Airport and put up a number of hundred scientists in that resort, working a shuttle bus from resort to website. We obtained some architects and builders in, an entire load of apparatus, assist to maneuver in from the military, help from universities across the UK, and an assay in place. Inside 16 days we have been testing scientific samples for the UK.

The dimensions of the collaboration endeavor was not like something I’ve ever seen earlier than and hopefully not like something I’ll ever be concerned in main once more. Medicines Discovery Catapult was on the coronary heart of it. We had unbelievable assist from Alderley Park, landlords, firms like AstraZeneca, and universities reminiscent of Manchester and Leeds.

There are too many individuals I may thank for making it occur. I feel everyone acknowledged, as scientists, that doing a little science to assist the pandemic was higher than sitting at residence worrying in regards to the pandemic. There was an actual mobilization at our website, the UK and internationally, of scientists who may assist. We had senior professors again in tissue tradition hoods prepping samples into vials as a result of they needed to assist.

It was heartwarming to see how a lot this trade pulled collectively. From diagnostic suppliers to automation specialists, to pharma firms, to not for income, to universities, all have been doing what they may do to assist. We coordinated the efforts at Alderley Park, as one in every of three nationwide labs. Whereas I’m now not straight concerned, that lab is continuous and has now achieved greater than 20 million samples and employed 700 folks at anyone time. Nicely over a thousand workers have been skilled in tips on how to do diagnostic testing. Hopefully, that’s one thing that has helped the UK and may depart a unbelievable legacy for the long run.

Like all of us in March 2022, the world got here roaring at us. We’re a provider of pattern preparation, pattern processing, and pattern entry applied sciences that embody storage programs, labware, and processing tools, at temperatures from ambient all the way down to -80 levels celsius. We’re deployed at educational establishments, analysis hospitals, and enormous pharma all over the world.

As March hit us, we have been impacted by defending our staff, shifting remotely to work offsite, and the problem of supporting and deploying essential tools within the COVID analysis pipeline. Every day was an fascinating, unexplored avenue for all of us.

Our tools, primarily based on the place it sits in R&D organizations, was essential to maintain working and our staff wanted to be there. From our discipline service engineers to our gross sales of us, everybody wanted to determine methods to try this. Many people labored from our residence workplaces, however many people couldn’t. Our manufacturing amenities continued to work. We have been open each day of the week since March 2020 and had to determine how to try this.

On high of that, we have been additionally within the provide chain, and far of our tools and applied sciences have been wanted by new labs. We needed to handle and allocate merchandise and assets rigorously.

We had way more demand than provide. We get up each day making an attempt to assist the world, our households, and our mates be wholesome, stay longer, and survive issues just like the pandemic. Thank goodness we have now that in our hearts and souls and we work to try this.

Collaborations got here at us rapidly. For instance, there’s one we’re doing now with a startup at Harvard and their associate Rhinostics, an organization right here in Wayland, Massachusetts, that created some different swab testing {hardware}. This was deployed in very excessive volumes as a result of testing demand went up. We now have robots and automation that may make these items work in excessive throughput labs.

They got here to us with the problem to take away the tops of check tubes. We obtained along with LabElite DeCapper applied sciences and created an automation that enables caps to be capped and decapped in a really, very excessive throughput method. That relationship continues.

The pandemic continues to take turns left and proper. Even because the throughput wants are diminishing and we make progress on the virus, we’re challenged with different circumstances. Our storage merchandise, the place we retailer analysis samples at as much as -80, proceed 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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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.

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.


Image Credit: fotogestoeber/

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.

(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.

Artificial Intelligence

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(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.

(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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