Two new HHS programs to help with complicated health challenges

Tom Temin Well, let’s start with the first one, Artificial Intelligence. I don’t think any agency grant activity research project doesn’t address artificial intelligence today, testing drugs and getting drugs approved in a 10,000-page, 10-year effort. What are you trying to do here?

Andy Kilianski Yes. So, once again, thank you for the opportunity to be here. And you’re right, many of the efforts we’re making across government are tied to the world of artificial intelligence. So what we’re trying to do in the Catalyst program, which is the tools that enable AI for drug development, is really increase our chances of success when drug candidates enter the clinical pipeline. Typically, there are a few years of preclinical research beforehand, and this occurs with computational models, but also with animal models and other types of wet lab experimentation. And this process means that less than 10% of all medicines that enter the clinical trial process are licensed. Therefore, we have many flaws in both the efficacy and safety of these medicines. And so what we want to do in the Catalyst program is really create an environment where we can use computational tools to better predict human outcomes based on these preclinical experiments.

Tom Temin So the idea would be to prevent the 90% or at least a good portion of the 90% from entering the pipeline in the first place.

Andy Kilianski Exactly. And what we really haven’t been able to do well in clinical trials is represent the diverse population across the country. So what we’re going to do in the cannabis program is really emphasize bringing in fundamental human data that is representative of this country from a genetic and environmental context so we can model again in silico with computers, how these pharmaceutical candidates might impact a range broader population.

Tom Temin And is this just a feel-good DEI kind of thing, or do we know that there are different effects of a given drug on different segments of the population?

Andy Kilianski No. The effects of drugs vary widely according to genetic origin, environment and a number of different factors. And typically in preclinical models, we use animals, inbred animal models and things like that that don’t have any population genetic diversity. And we’re using these tools, which are proven not to recapitulate human physiology. Also, when we get into something like a phase one clinical trial. There are usually dozens to hundreds of patients. And in a safety assessment, these are healthy people. Young adults, middle-aged adults, 18 to 35-year-old types, and typically don’t accurately represent the broader population diversity, both in terms of their genetic origins but also the diseases they have. And that carry comorbidities, in addition to environmental factors.

Tom Temin Well, the chimps will thank you for it, but it looks like there are datasets that can actually be used to digitize what used to be done to humans and animals.

Andy Kilianski Exactly. So we’re looking to really innovate in the ways that we collect data from human models and human subjects, but also from a wide variety of these 3D printed organs that we’re also investing in. better simulate our own physiology as humans.

Tom Temin And is there then the assumption that what we can know about what has already happened, given all this data about effects, can be supported in designing new medicines from the start?

Andy Kilianski Yes, 100%. The goal of the program is to really innovate how we get first-in-human testing approval. So we do all these experiments in advance, and then a drug developer will go to the FDA and present a package called an investigational new drug package that details how they evaluated the safety of their pharmaceutical candidate. And they ask for approval to enter a phase one clinical trial. Typically, these experiments involve animals, varieties of different types of animal models. And in this area of ​​drug development, little has changed in the last 50 years. We still use many of the same tools we used as we rapidly innovate in the early parts of drug discovery, target selection, taking a billion chemicals and narrowing that down to 10 potential candidates for a given target. And what we’d like to do is really bring that innovation into the safety assessment part of the drug development process.

Tom Temin We’re talking to Dr. Andy Kilianski. He’s a program manager at the Health Advanced Research Projects Agency. That’s part of Health and Human Services. And the other program we were talking about is the computing systems needed to design vaccines, which I think is also very demanding. computing. What’s going on with this program?

Andy Kilianski Yes. So, Tom, you’re seeing a theme here in the programs that we’re launching. The focus of my team and our portfolio is really trying to make biomedical development and healthcare research more predictable. So we do a lot of trial and error on these things, especially on vaccines and therapeutic projects. And so what we would like to do, based on our shared experience with COVID 19 and other emerging infectious diseases, is we need things on the shelves before a future public health emergency. We need things that can attack multiple infectious diseases at the same time and do so in a way that makes these products commercially viable, so that we can maintain the ability to respond to things in the future. So the Apex program is focused on using these computational tools and looking for broadly immunogenic protein designs on computers, and then evaluating them in animal models and in Congress.

Tom Temin And I heard about the last pandemic, someone said, I forget who it was, that the ability to quickly develop the vaccine that we got for COVID was because this virus belonged to a family of viruses that we had already made vaccines for. That’s why it only took a year or so. But there are 15 other types of viruses that entered the scene, which were prepared by humanity.

Tom Temin That is true? And could this work that you’re doing branch out from the kind of viruses that we’re used to, to those that haven’t yet spread into the wild and started killing people?

Andy Kilianski Yes. I’m actually a coronavirus researcher by training, and I did some of this work on the original virus before the COVID-19 pandemic. And then you are absolutely right. We knew a lot about the coronavirus, the structure and function of proteins, and so we were able to design these vaccines relatively quickly. There are other viral families that we know much less about, but we know in general what this evolutionary diversity looks like. Therefore, our program seeks to climb this evolutionary tree to find those true common denominators among viral families and target them from a therapeutic vaccine design perspective. So this way, we can be prepared for things that we already know exist and build therapeutics and vaccines that work against a variety of different current threats. But then, if nature throws something else at us that we don’t see today, we will have a reasonable expectation that the tools we develop will work against those threats as well.

Tom Temin Yes, this isn’t exactly artificial intelligence, but it is replacing something that is wet with something that is digital.

Andy Kilianski Exactly. Starting with leveraging these AI-enabled tools and really leveraging our best possible multi-target design, as opposed to the way we currently do these things, which is actually one pathogen to a therapeutic or a vaccine. And we would like to change this paradigm with the next program.

Tom Temin And now we discuss two different programs. What forms do they take? These will be research grants. How do you do this? Competitively with funding opportunities, that sort of thing?

Andy Kilianski Yes. So the Apex program was a competitive solicitation process. We have just reached the end of contract negotiations and this program has already started. And so we have five teams spread across the country that are made up of academic labs, NGOs and industry partners, and they are already working and generating data and trying to really go after this lunar breakthrough as we build a vaccine or therapeutic that works against everything. For our Catalyst program, we just announced that it launched a few weeks ago. And this is an open request and we are actively seeking participation from industry as well as academic and NGO partners in this program. So these are competitive processes and we analyze what is happening in the biomedical ecosystem and select the best proposals that we receive.

Tom Temin And how do you know that you are always counting on the best minds in this biomedical ecosystem? Because there is a very deep level of players. There are the big well-known pharmaceutical companies. And they have really good chops. And there are also the big, well-known medical schools, and they do too. But there are a lot of startups and a lot of mid-tier companies that can do something, and they contract the research and they buy the research because they can turn it into something that they can manufacture, at various levels. What are your mechanisms for ensuring you’re reaching every potential brainiac out there?

Andy Kilianski I really appreciate you having me because this is one of those mechanisms. Yes, I think we face the challenge, as a brand new agency within the US government, of marketing outreach. What we do, what kind of research we fund and why it’s cool to work at our age, and why it’s important to go after these kinds of lunar targets. So we’ve received proposals from some of the biggest companies, the biggest academic labs that you’ve probably heard of. But we received proposals from the world of startups. And in fact, with the Apex program, we are funding a biotechnology startup that is leading one of these teams. And so we really want to reach, as you said, all strata of research that is happening across the country and especially in the AI ​​machine learning space. Many of these companies may be developing a tool that works for an engineering or cybersecurity problem. We would like to help companies with non-dilutive capital through our page to truly pursue biomedical and health outcomes.

Tom Temin And for someone who is a long-time researcher like yourself. Coming to ARPA-H as a program manager must be like being in the cockpit for a while.

Andy Kilianski It’s incredible work. So I worked in government for many years. I was out of government for a few years. And returning as an outreach program manager is incredibly exciting. I have the best job in the government. I can find brilliant people to work with to try to tackle these really difficult biomedical challenges. And so, yes, I am very lucky. And I’ve been in government and realized what an excellent job I have here.