R&D: Learning to Share
Nonprofit and for-profit R&D need to take a good look at one another. What one has, the other lacks. Scientists searching for drugs for neglected diseases typically work in open, collaborative systems and share information, but they lack the resources to heavily invest in large-scale clinical trials. On the other hand, when profits are at stake and competition is fierce, Big Pharma researchers very often plug in to their well-financed vacuum—even though the answers may not be found there.
Scientists from the two worlds of research have a lot to learn from one another. But this time, nonprofit R&D execs are leading the charge. They are showing Big Pharma how to collaborate for the greater good, starting with drug safety, and in the process, rewriting the rules for research and development everywhere.
Mindful of this, Novartis, with Paul Herrling at its helm, is fighting to make all areas of R&D more efficient by advocating collaboration and communication. With Novartis, Herrling helped start the SNP Consortium, the first major collaboration between prominent research institutions and pharma companies. Throughout his career, he has been able to bring together important R&D players. When Sandoz Pharmaceuticals merged with Ciba-Geigy to form Novartis in 1996, he led the companies' integration and developed a new research model that had car engineers working side by side with biologists.
When we caught up with Herrling—who in addition to his day job at Novartis is a professor at the University of Basel, Switzerland—he gave us a lesson in R&D (there was even a pop quiz). Herrling explained how the Novartis Institute for Tropical Diseases (NITD) is reaching out to other companies and utilizing the newest technologies to research neglected diseases. Research institutions, pharmas, and agencies: Pick up your pencils and start taking notes.
Do you think neglected disease sets the standard in terms of efficiency? Or is it kind of behind the pack?
If you are talking about neglected diseases in the developing world, like malaria and TB, then clearly we are on a major catch up. For example, the last tuberculosis drug that was put on the market was some 30 years ago. Of course, the reason nobody has worked in TB is that you can't make any money—and drug companies are commercial organizations. We have to get a return on our research investment.
Currently, there is only a handful of companies doing clinical research in neglected diseases, and Novartis' Singapore Institute is the most consistent. We've applied the most modern drug-discovery technology to find new drugs for diseases like TB and dengue.
What new techniques are you using in this area?
We only recently have the complete sequence of the genome of pathological organisms like TB and malaria. That means we can now apply all the tools of genomics to find characterized targets.
Up until now, drugs for TB were found by throwing a compound at bug cultures to see which ones died, with no attention to targets or mechanism of action. The only questions were, Does it kill the bugs and does it have acceptable side effects? That's much simpler than tweaking a subtle biological mechanism within the human body.
It turns out, however, that TB is a highly sophisticated organism that has maneuvered itself into a corner of evolution. Its specialty is to survive only in people, so it has evolved many mechanisms that allow it to do so. And one of the most perplexing and difficult—in terms of developing treatments—is that TB mycobacteria have learned, when they encounter negative conditions, to stop dividing and hide in the tissue. And they can stay there and then grow again after 50 years.
So now we are trying to understand how they do this. Just to give you an example, when they stop dividing and hide, they shut off a significant part of their metabolism. Most of the machinery being used for cell division, for instance, is turned off to save energy, which means that antibiotics don't work anymore because they specifically address growth mechanisms.
If you are interested in understanding how they hide, one thing to do is to map their genetic expression—which genes are turned off and which genes stay active during the latent phase—and try to derive targets. Now, for the first time ever, we are applying the same tools that we use to find cancer or Alzheimer's or diabetes targets to these bugs.
Are these expression maps used often within the industry?
In the infective area, of course—the genomes of all of these pathogenic organisms are being published constantly. But there are very few people working in TB—four or five companies.
Now another very interesting point is that most of the original antibiotics were natural compounds because—well, maybe I can ask you a little test question. Who invented antibiotics?
Was it Alexander Flemming?
Well, a lot of people think it's Flemming, but actually that's wrong. Penicillin was invented by bugs against bugs through millions of years of evolution. Antibiotics originally were secondary metabolites of bacteria, which they were using to kill each other. And Flemming learned relatively late that you can find within natural organisms compounds that can kill others. That was the origin of the human use of antibiotics.
Now we try to synthesize them. Today we have our big libraries with a few million compounds. Whenever we select a new target out of the genome, we first test our library against it and see if we get hits, compounds that interact with that target. If we do, we take those as the starting point for a chemical-optimization program to transform the hits into what could be a drug.
In the case of both TB and dengue, our compound libraries very often do not contain any drugs interacting with these targets. It seems that because nobody worked on these bugs for at least two generations, nobody made any compounds against them. And given that most antibiotics used to be natural compounds, made by bugs for bugs, the synthetic libraries do not contain any compounds that interact with these bacterial targets.
What this means is now we have to apply the most sophisticated rational-chemistry mechanism, proteomics. We must determine the three-dimensional structure of those enzymes or signaling molecule pathways that we want to attack receptors, and then design a new compound or family of compounds that will interact with those. We always have to create new libraries.
This is another way that the absolutely newest form of structural chemistry, rational chemistry, is being rolled out against neglected diseases, which was never the case before. At the Novartis Institute for Tropical Diseases, with our partners, we have solved the three-dimensional structure of at least three dengue enzymes, which was essential because that was one of those areas where we didn't find any lead compounds.
The philosophy behind the NITD is to take sophisticated new drug-discovery mechanisms that are developed for our mainstream business and systematically apply them to the pathogens of neglected diseases.
Given that there are not a lot of therapies available and the unmet need for treatment is so urgent, are you implementing any new tactics to speed up the very long discovery and development time?
Well, if I did, I would apply it to the commercial part first, because it has the same problem. Anything to shorten the process for drug discovery and development and to reduce the attrition rate would have a monumental impact on the whole industry.
Originally, we thought that developing treatments for TB and dengue might be faster, because it's simpler to kill a bug straight off than to tweak a complex biological mechanism in the human body. But we realized that was a na´ve illusion when we looked at how intimately the pathogen and the host are interconnected.
I've spoken to other researchers about their drug-development innovations, and they've talked about doing Phase I/II or Phase II/III.
That's the one thing that Novartis was pioneering—with the proof of concept in man—for all our drugs going into the clinic. It is in contrast to what we were doing before—Phase I in normal volunteers and looking at the side effect profiles, Phase II dose-escalation studies, and Phase III for efficacy.
Because we understand the molecular mechanism of action in our drugs, the very first time we go into human beings, we try to see if the scientific hypothesis that we have made in preclinical research translates to the human situation. An example is the Alzheimer's vaccine. We try to make the human body make antibodies against beta amyloids. Well, at the same time we are now testing for safety, we are also testing that proof of concept. Previously, that would have been done much later in the process.
For several years, we have been systematically doing that for all of our drugs going into the clinic. Actually, even during the selection criteria—if the development and research teams cannot come up with a scientific readout that indicates that the working hypothesis translates to the human situation, these drugs now have a lower priority than the ones that do have such a concept.
This is a very important go/no-go criteria for full development before it costs the hundreds of millions that it does in Phase IIs and IIIs. If I can put the drug in people, I should see this or that enzyme go up or down, and if it doesn't happen, then the drug is dead then and there.
In terms of toxicology and safety studies, are there any new ways of testing early on that are going to be particularly applicable?
Yes. First, a lot of things that used to be done only in animals can now be done earlier in vitro. So there are quite a number of in vitro assays developed that can predict prohibitive side effects in people.
Second, just like we do expression patterns of drugs with the clinical studies, the toxicologists are generating databases of drugs that fail for toxic reasons and seeing if there's a typical genetic fingerprint and other commonalities. For example, the family of genes that would lead to liver failure.
Now, if you could do that earlier, possibly in animals or even in in vitro situations, rather than waiting until you are in expensive human studies, you could eliminate drugs that have a lower probability of survival because of these side effects.
There is a big European program that we are discussing to share those databases—they are proprietary and they are the historical experience of that company with particular drugs. The question arises, if these drugs are not going to be competitive because they cannot be translated into real medicine, could companies be convinced to pool this data and thereby find common genetic patterns that are predictive of toxicology much faster than if each company does it on their own? That is one of these things that people are thinking about.
Novartis is already starting to contribute some drugs with expression patterns, and several other companies are also signing on.
So it's moving forward.
Yes, hopefully. Of course, the scientific question that's still open is, Will we find sufficiently predictable patterns to really be able to say with some level of confidence that one drug should not be further developed, while that one is OK? But these methods all need to be validated and confirmed. And what will be great is if we can get a sufficient level of reliability that the regulatory authority accepts these methods. That might help to reduce the number of animals used in safety studies.
It's still too early to call. As usual, we will learn by experience that there are some classes of drugs for which it works very well and others much less. Especially for completely new mechanisms, it will be more difficult.
How is this similar to FDA's Critical Path Initiative that's encouraging companies to share information?
Oh, this is very similar, but it is under the auspices of the European Union.
So it really does seem that the future of R&D can be one of collaboration at certain points.
Oh, yes. Novartis was one of the companies that started the SNP Consortium of cross-company collaboration, a joint venture between Wellcome Trust, the Sanger Institute, the Whitehead Institute, the Genome Sequencing Center, Cold Spring Harbor, Stanford University, and 10 major pharmaceutical companies. It was the first time that several pharma companies pooled their resources to make this map as fast as possible, and they made it available both to academics and to themselves to get more predictable drug discovery. The initiative we just talked about in safety goes along the same lines.
It's interesting that in the neglected disease area, collaboration and partnership is standard, with a whole range of public–private partnerships. But that idea seems to be translating into the for-profit world.
Well, there are different kinds of collaborations. For the SNP safety databases we said, "If each of us does it alone, we will not have the answer because we don't have enough data to compare. And it'll be so expensive, we'll ruin ourselves. So let's do it together."
Now, the neglected disease area has another aspect that makes collaboration easier: It's mostly not-for-profit. So there is no commercial competition. As you know, the Drugs for Neglected Diseases initiative and Medicines for Malaria Venture all have the not-for-profit concept as part of their business model. They are not allowed to make money with these drugs that they develop. The commercial competition that is traditional between pharma companies does not appear.
Since the money that pharmaceutical companies allocate to neglected diseases will not generate returns, by definition it has to be limited because our shareholders want to have returns. They accept that we invest some part of our resources into noncommercial neglected diseases, but there are limits. So it is even more important that the resources that we can allocate to these big diseases of the developing world are used in the most efficient way possible. Therefore, we want to avoid redundancies and share as much information as possible.
It's not only the pharma companies that are not investing in neglected diseases, unfortunately. Agencies like the National Institutes of Health or Medical Reserve Corps are also not funding research into these diseases because they feel that it's public money that needs to be applied first to cancers and Alzheimer's and so on, and not to diseases that are primarily occurring in other countries. So even the basic science at universities is neglected.
The community of companies that are now reinvesting in these neglected diseases have to build on a very thin, basic science base. Again, it is extremely important that we use the resources that we have as efficiently as possible and try to coordinate and not all work on the same idea or the same thing.
There are difficulties with that, but I'm currently discussing with other colleagues in the industry a concept for how we could do it, at least to a limited extent, without getting into antitrust problems and so on.
Where can we learn more about that?
It's not yet public because I'm still learning, and it's not finished. Actually, I've worked for two years on this project, and it has been very difficult to convince people. But we have a number of pharmaceutical companies interested, and we might have the concept sufficiently advanced so that we can at least discuss it in public soon.
Additional contribution by Alissa Piccione
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