Interview with Professor Michael Pollastri

Michael Pollastri discusses the virtues of open science in neglected tropical disease drug discovery

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In this interview I speak with neglected tropical disease (NTD) scientist, Professor Michael Pollastri (Northeastern University, MA, USA), about his research and the launch of his group’s new, crowdfunded, data sharing portal where NTD drug discovery labs around the world can deposit their work, with the ultimate aim of coordinating research efforts in this important and resource-limited field.

Can you briefly describe your research in the field of neglected topical disease (NTD) drug discovery?

My laboratory is focused on the application of medicinal chemistry in the discovery of new leads and drugs for NTDs. Our program identifies compounds that have been developed for diseases such as cancer or inflammation (typically kinase inhibitors) that show a modicum of potency against the parasites that cause human African trypanosomiasis, Chagas disease, leishmaniasis, filarial diseases, schistosomiasis, and giardiasis. Once we identify “hit” compounds with some minimal level of in vitro potency, we re-engineer them for increased potency against the parasite, reduced toxicity against host cells, and physicochemical properties that are appropriate for a given indication (such as brain penetrance for HAT).

You recently founded the NTD Hybrid-Open Data Sharing project. Can you tell us what this entails and what you hope to achieve through this initiative?

The field of NTD drug discovery is very small, and because funding is tight, it is natural for teams of investigators to become competitive and siloed. In fact, this is the worst thing to do, because the likelihood of duplication of effort increases, especially in light of the various publically-available compound screening sets and data (such as the KinetoBox or MalariaBox from GSK, the GSK antimalarial data set, and data from our own kinase-targeting HTS against T. brucei). The data sharing project is intended to provide a safe environment for NTD researchers to share information about compounds and data in real time (i.e., not after publication); this environment consists of a Collaborative Drug Discovery (CDD) Vault, where participating members agree to confidentiality terms, and agree to deposit data as the data is generated. Such data consists of compound structures, ADME data, in vitro activity, etc. We raised funds to cover the cost of the Vault, and have some funding available to incentivize collaborators who are interested in accessing, for example, ADME or pharmacokinetics or synthetic capabilities.

What originally prompted you to set up this data sharing portal?

I was thrilled, as were many, that GSK released their Antimalarial HTS results in 2010. As I was looking through the data and selecting chemotypes that were of interest, I realized that I had no idea whether anyone else was already working on the chemotypes that I’d selected. For all I knew, people were all focusing on the same chemotypes, encountering the same challenges, and wasting the extremely limited funding that we are all afforded. Having been a former pharma medicinal chemist, I recognized that it would be difficult to get other medicinal chemists to share data openly; and so I tried to design the data sharing project in such a way as to reduce investigators’ reluctance to share data with each other.

Many scientists may feel dissuaded from sharing their data online due to the perception that it might reduce their chances of publishing the data in a high-impact journal at a later date, in addition to the fact that they may wish protect their intellectual property. Is this an issue and, if so, how might scientists be encouraged to contribute their data to the portal?

Indeed, this is a perceived issue, but in our case, the data that is shared is actually not out in the open, per se – it is only accessible by others who agree to the same confidentiality terms, and who also agree to share their own data in this manner. So there’s nothing precluding publication or patenting.

Are there any mechanisms in place to ensure that the data uploaded to the portal is complete, accurate and reproducible?

This is a real challenge in general, but all of the current participants in the portal are using the same assays (from the same parasitology lab), and so there’s high confidence in comparability of results. If and when we expand to other biological collaborators with different assays, we intend to provide information about what protocols were used to generate which data – though this doesn’t necessarily guarantee reproducibility, it definitely provides transparency.

In what ways does this initiative compare to similar projects in this area, such as Open Source Malaria? The OSM project is an amazing undertaking. The commitment to complete openness is remarkable, and indeed, it is changing the way many think about doing NTD drug discovery. Ours differs simply in that, in order to access the deposited data, we require people to commit to keeping the data in confidence (though they can (should!!) use it for driving their own decision making), and to depositing their own data. The OSM project allows literally everyone to access their data and project meetings, requiring nothing in return.

How do you envisage the classic drug discovery model will evolve over the next 10-20 years in the field of NTD research?

I am hoping that as people continue to move to the field of NTD drug discovery there will be reduced concern about protecting intellectual property (since it’s very unlikely that any money will be made!) and more towards helping each other out. I envision a community of NTD drug hunters who share their data so that compounds that show activity against one disease might be tested against other pathogens – this is an approach that has really paid off for my laboratory! This community of NTD drug discovery groups will be working towards shared goals, in terms of robust target-product profiles and consistently applied disease models. I think that the super-secretive pharma drug discovery model just is not the right way to expect to move NTD drug discovery forward – there are far too little resources available to allow a broad (17 NTDs!) and deep drug discovery effort if these efforts are completely separate, so we must keep an open mind about ways in which we can leverage and maximize each other’s results.

For more information about the data sharing portal, please visit Michael's website.

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Hannah Coaker

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