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a16z Podcast | Move Fast But Don't Break Things (When It Comes to Computational Biology)
26 segments available
The mindset of "move fast and break things", while great for code, isn't exactly great for the human body. So adding computation to biology -- especially in the slow-moving pharmaceutical industry, where drug approval can take years -- brings with it both opportunities (like drastically faster discovery and assessment) and challenges (the need for hard evidence, not just soft-ware). But there's more: We don't want just better outcomes for healthcare. We want better outcomes at a cheaper price. And that's where machine learning comes in. The benefits of such computation -- i.e., software -- can provide a powerful, frictionless, and far more cost-effective tool for biopharmaceutical research ... but it requires data. So who provides that data? Is it the pharmaceutical companies, or the payers (insurance)? How are organizations incented to overcome intellectual property silos in sharing their data? Especially since it was only relatively recently, Jeff Kindler (the former CEO of the world's largest pharmaceutical company, Pfizer) reminds us in this episode of the a16z Podcast, that the FDA even allowed data to be put in computers vs. on paper. But there's a reason the self-driving car was pushed out of the software and not the auto industry, argues TwoXAR co-founder and CEO Andrew Radin -- and it has to do with the unique nature of the developer's mindset applied to novel problems. The deterministic nature of Moore's Law -- it's not a matter of if, but when -- plays a role too, observes a16z bio fund general partner Vijay Pande. There are things that big data and simulations will be able to accomplish that a hundred lab experiments on animals can't. Still, the two mindsets will have to merge, so we can move fast ... but without compromising quality, safety, and reliability. That's the big difference between computer science and biology after all. image: mattza/ Flickr
Segments Timeline
Introduction to Computational Biology
In this segment, Michael Copeland introduces the a16z podcast episode focused on computational biology. He welcomes guests Jeff Kindler, former CEO of Pfizer, and Andrew Radin, CEO of TwoXAR, to discuss how technology can improve healthcare and the pharmaceutical industry. The conversation sets the stage for exploring the intersection of computation and biology.
"welcome to the a 16z podcast I'm Michael Copeland and we are here in the room with three people to talk about computational biology and how compute meets biology and and generally speaking how healthc..."
Challenges in Healthcare Innovation
Jeff Kindler shares insights on the difficulties faced by the pharmaceutical industry in adopting new technologies. He draws an analogy to Hollywood's evolution, explaining how pharma is transitioning from a fully integrated model to one that embraces outsourcing and collaboration with external partners to enhance efficiency and innovation.
"it's great thank you we have seen technology and software in particular you know from our vantage point seep into all kinds of industries right so bursting it in finance we're seeing it in driverless ..."
The Shift Towards Outsourcing in Pharma
Kindler discusses the historical reluctance of the pharmaceutical industry to outsource due to profitability and control concerns. However, he notes that increasing financial pressures are prompting companies to reconsider their strategies and explore external partnerships for better efficiency and cost management.
"to better health in the end but better therapeutics better you know testing for that matter maybe Jeff let's start with you why is this problem so hard and how you you've been in this space for a long..."
Empowering Startups with Computational Resources
Andrew Radin highlights how startups can leverage on-demand resources in computational biology. He explains the advantages of accessing expensive infrastructure without the burden of ownership, allowing smaller companies to compete with larger firms by utilizing services as needed, akin to AWS in the tech industry.
"a similar shift for many years until even relatively recently they were one of the full one of the few fully integrated industries in the sense that they did everything in-house from Discovery through..."
The Role of Technology in Pharma's Future
Radin emphasizes the current technological advancements that align with the pharmaceutical industry's needs. He discusses the importance of standardization and automation in pharma processes, suggesting that the integration of modern technology can lead to significant improvements in efficiency and outcomes.
"with the way they did things but what's happened in the last few years is they've come under greater earnings pressure they're really looking at their balance sheet or income statement and they're com..."
Cloud Computing and Pharma's Transformation
Vijay Pande discusses the gradual adoption of cloud computing in the pharmaceutical industry. He explains that while there may be initial hesitations regarding security, the benefits of cloud services, including cost-effectiveness and improved security, are becoming increasingly recognized, paving the way for broader acceptance.
"10 minutes worth of computation and then release that resource and don't have to pay for it again that enables startups and and small companies to do things to have all the types of resources that the..."
Revolutionizing Animal Models with Technology
Pande introduces the concept of cloud biology, where real-life experiments are conducted using automated systems. He explains how this approach enhances reproducibility in biological experiments, addressing a significant challenge in the field and demonstrating the potential for technology to improve research outcomes.
"there and there may be that pressure now but breathing things back so for example the cloud and the banking industry the banking industry is like whoa whoa whoa why would we ever do that turns out now..."
The Intersection of Programming and Biology
The discussion shifts to the complexities of integrating programming with biological research. Pande highlights the challenges of ensuring reproducibility in experiments and how programming can help standardize processes, ultimately leading to more reliable results in the field of biology.
"is cheaper and better then it's actually a very strong value proposition and something being very new will mean that it won't have a mediant adoption but as people start to see it I think they'll star..."
The Rise of Cloud Biology
In this segment, the discussion revolves around the concept of cloud biology, which involves conducting real-life experiments through systematized processes, often driven by robotics. This approach enhances reproducibility in biological experiments, addressing the current challenges of variability and unreliability in traditional methods. The integration of programming into biology is highlighted as a transformative factor in research efficiency.
"today with it and and sort of where do we head there are several companies in this space that are pushing the envelope of cloud biology and um when I think about it I think of it as doing real-life ex..."
Software as a Research Tool
The conversation shifts to the role of software in biological research, emphasizing its capacity to analyze vast amounts of data quickly. The speakers clarify that while software aids researchers by providing insights, human interpretation remains crucial. This segment underscores the iterative nature of software development and its potential to accelerate biological research through rapid experimentation and adaptation.
"ethos of programming into the biology realm and that's part of what we save when we talk about it being better one of the things that that fascinates me though is that programming is programming right..."
Big Data's Impact on Pharma
This segment explores the significance of big data in the pharmaceutical industry, highlighting the potential for combining siloed datasets to gain unprecedented insights. The speakers discuss the evolution of data analytics in healthcare, referencing IBM's acquisition of Trevean and its implications for drug development. The conversation emphasizes the necessity of human judgment in interpreting data while acknowledging the transformative power of structured and accessible data.
"so for me software is is it is a tool it's a very powerful tool it's a way to accelerate the process and I think also there's there's a there's a part about software development that is this very iter..."
Better Outcomes at Lower Costs
The discussion here focuses on the dual goal of achieving better health outcomes while reducing costs in healthcare. The speakers draw parallels between advancements in machine learning across various industries and their potential applications in healthcare. They emphasize the importance of data availability and the need for human oversight in leveraging machine learning to improve healthcare delivery.
"the end of the day what we want is better health outcomes so I I wonder if you've seen this story before in another industry or or maybe the other way to describe it is like what are we looking at and..."
Data Sharing in Pharma
In this segment, the conversation addresses the challenges and opportunities of data sharing within the pharmaceutical industry. The speakers highlight the disparity between the data held by pharmaceutical companies and payers, suggesting that collaboration and data sharing will be essential for future advancements. They discuss the potential for innovative approaches to overcome intellectual property concerns and the necessity of leveraging collective data for improved healthcare outcomes.
"couldn't do before but there's certain requirements we need the data and we need to be able to still have the right directions to point this to and so the human part is certainly going to be there but..."
The Future of Big Pharma
The final segment contemplates the evolving landscape of the pharmaceutical industry, questioning whether the traditional model of Big Pharma will adapt or diminish in relevance. The speakers reflect on the historical context of biotech acquisitions by larger pharmaceutical companies and speculate on the future dynamics of the industry as data sharing and technological advancements reshape drug development.
"different ways yeah or they don't even have to release the data one can run a eye on the data in behind their firewall and use that to generate features or the things that could come out so I said I t..."
Innovative Models in Pharma
This segment highlights innovative models in the pharmaceutical industry, such as the role of foundations in drug development. It discusses how organizations like the Cystic Fibrosis Foundation are pushing for new drug discoveries and how these models could reshape traditional pharmaceutical practices.
"much about cost you know add another hundred million dollars to a trial so what if it's going to add billions of dollars to the drug sales that's changed the risk of drug development drug discovery ha..."
The Future of Drug Development
In this segment, the discussion focuses on the potential for personalized medicine and the challenges of drug development. It emphasizes the need for accurate diagnostics and the integration of various data sources to improve treatment outcomes and efficiency in the pharmaceutical industry.
"think some of them are on the way to do that others are still thinking in legacy terms and also I don't think it has to be mutually exclusive I think there will be changes in pharma but also there's j..."
Towards Personalized Medicine
This segment delves into the vision of personalized medicine, where patients receive tailored treatments based on their unique biological data. It discusses the current limitations and the future possibilities of achieving this goal through advancements in data collection and analysis.
"about tech an interesting little experiment that you can do to sort of test the degree of maturity with regard to outsourcing is to ask firm of people what is the core competency of a pharmaceutical c..."
The Role of Technology in Healthcare
The conversation highlights the role of technology in transforming healthcare delivery. It discusses the demand for on-demand services and the need for the healthcare system to adapt to consumer expectations, emphasizing the potential for disintermediation and improved pricing in the industry.
"more toward personalized medicine - you talk about from drugs but I mean there's always an orphan for a drug probably yeah you know there is some really tantalizing possibilities here that 80% of all ..."
Challenges in Healthcare Transformation
In this concluding segment, the speakers address the complexities of the healthcare ecosystem and the historical reluctance to change. They discuss the FDA's recent acceptance of digital data entry and the implications for the future of healthcare, emphasizing the need for quality and control amidst evolving demands.
"yeah and I think we need to really over time they also build enough data to be able to pull those things off I mean like for me ultimate personalized medicine as I as I walk into my pharmacy I say I'm..."
FDA's Trust in Data: A Historical Perspective
This segment provides a historical perspective on the FDA's reluctance to accept digital clinical data, highlighting the slow evolution of trust in technology within the healthcare sector. It underscores the importance of quality and integrity in data management and how this has impacted the speed of innovation in drug development and healthcare delivery.
"it's an incredibly complex ecosystem with you know thousands of different interests sometimes in conflict whether it be hospitals doctors payers patient groups pharma companies the government it's als..."
Simulations vs. Animal Testing
The discussion focuses on the potential of data science to replace traditional animal testing in preclinical studies. It explores how computer simulations could provide more accurate predictions for human responses, suggesting a future where animal testing is minimized or eliminated, thus revolutionizing the drug development process.
"would all agree is kind of silly because it's much more reliable than paper but just the fact that that only happened recently suggests that when you're in a in an industry with a regulator that is qu..."
The Shift Towards Computational Solutions
This segment anticipates a future where computational solutions are integrated into healthcare, emphasizing the need for rigorous evidence to ensure safety and reliability. It discusses the cultural shift required in the industry to embrace these changes, highlighting the importance of balancing innovation with patient safety.
"being right so what does that mean we're talking about you know the FDA right we're gonna we're gonna convince the FDA we're just going to put it all in the computer then we're going to drop it in a p..."
Bridging the Gap Between Tech and Pharma
The conversation addresses the cultural divide between Silicon Valley and the pharmaceutical industry, emphasizing the need for better communication and understanding. It reflects on past experiences where tech innovations were misunderstood by healthcare professionals and the necessity for both sectors to collaborate for successful integration of computational advancements.
"car and go to the pharmacy and stand in front of the machine and it spits out a pill just for me and maybe you won't have to go the farm yeah I think it's a blood test at home and something arrives la..."
Disruption in Pharma: Lessons from History
This segment discusses how disruption in the pharmaceutical industry often comes from external innovators rather than established companies. It draws parallels with historical examples of industry shifts and emphasizes the need for big pharma to adapt and embrace new technologies to remain competitive in a rapidly evolving landscape.
"today of interactions between the valley and Pharma I'd be in rooms where those two people were meeting and one speaking Greek and one speaking Latin there was a just a fundamental cultural divide the..."
The Unique Mindset of Software Engineers
Andrew Radin shares insights on how software engineers approach problem-solving differently than traditional industries. This segment highlights the innovative thinking that has led to advancements like self-driving cars and discusses the potential for similar breakthroughs in healthcare through computational thinking.
"challenges Pharma has had is its own success it hasn't had an existential crisis the way IBM did in the Gerstner era for example which is one of the few examples you can think of where a big industry ..."
The Deterministic Nature of Innovation
The final segment reflects on the deterministic nature of technological advancements, particularly in computing and genomics. It emphasizes the inevitability of progress in these fields and the exciting possibilities that lie ahead for healthcare innovation over the next decade, concluding with gratitude for the insights shared by the guests.
"thinking that culture that you know sort of stepping back from from the problem and just twisting it in a very different way I think is is quite compelling right there's just sort of this this differe..."