we use reaxys intensively for hit identification, hit-to ... · 2 case study dr. fabio c. tucci,...

CREATING NEW ASSETSEpigen Biosciences is a start-up pharmaceutical company that collaborates with academic groups to discover innovative drugs for a range of medical conditions, including renal diseases, cancer and CNS disorders. Co-founder Dr. Fabio Tucci met with Elsevier to discuss how Epigen researchers use Reaxys to support their application of advanced hit-to-lead and lead optimization methods.

Dr. Fabio C. Tucci, COO of Epigen Biosciences

“ We use Reaxys intensively for hit identification, hit-to-lead and lead optimization.”

CASE STUDY

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CASE STUDY: Dr. Fabio C. Tucci, Epigen Biosciences

Dr. Fabio Tucci, Chief Operating Officer and co-founder of Epigen Biosciences, has over 15 years of experience in drug discovery, medicinal chemistry and organic synthesis. Author or co-author of over 60 peer-reviewed publications and inventor in 14 patents or patent applications, he has had a very successful career, serving as a department leader at Tanabe Research Laboratories and Principal Scientist at Neurocrine Biosciences. Having founded Epigen Biosciences with Dr. Graham Beaton and Dr. Satheesh B. Ravula, he enjoys the challenge of being part of the discovery and development of new pharmaceutical entities.

“ Like any company in our position, whether we’re looking at synthesis routes, structure–activity relationships or patents, we need easy access to high-quality data.”

– Dr. Fabio Tucci, co-founder of Epigen Biosciences

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How would you describe the work you do at Epigen Biosciences?We call ourselves a biotech incubator. The intention when we founded the company was to be very flexible so that we could accommodate a variety of modes of operation. We have our own speculative projects, looking at interesting aspects of biology where we could see potential to target a particular receptor and have an impact on a certain disease. There are also projects where collaborators who don’t have the chemistry or drug discovery capabilities come to us with a particular target receptor for which they want to find effective drug-like compounds. Then we’d look for it and develop them into leads. Other collaborators might approach us with a compound or set of compounds from a screening program and look to our medicinal chemistry experts to develop the lead.

Ultimately, our focus is experimental chemistry. We have our wet lab here in San Diego, where we employ six medicinal chemists. Their everyday work consists of synthesizing new compounds, running analyses on them, optimizing their properties and so on. We develop small focused libraries for screening or work with commercial libraries. Our network of consultants supports us with biological profiling, physicochemical property profiling and so on.

How far through the drug development process do you follow a compound?The way we’re set up now, we can go all the way through early drug discovery, from hit identification to preclinical efficacy and safety testing. At that point, we would look for a partner to collaborate on advancing the project to human clinical testing or look for someone to purchase the concept.

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Pharmaceutical R&D is well known to be extremely data intensive. How would you define your data requirements?The answer to that question definitely depends on what stage of the early discovery process we are at, but I will attempt to summarize some of the challenges.

In terms of focused library creation, we have to identify a robust synthetic method to be able to efficiently proceed. Our resources are limited so we want to achieve synthesis in as few steps and with as high a yield as possible. It saves us a lot of time and a lot of optimization processes if we can understand the synthetic methods that have been used in the past with similar classes of compound—that historical data and all those published experimental procedures really inform our planning.

When we’re figuring out what types of molecules to synthesize or what analogs to create from a hit in a focused library, we need data on compounds that target the same or homologous receptors. That gives us an understanding of the structure and properties we need and

helps us steer our design in the right way to get the bioactivity we want. At that stage, we really need to have the data in a form compatible with computational tools because we have to try to figure out the best analogs to synthesize.

Intellectual property information is of course crucial to us. We always have to be aware of that. Our molecules have to be novel. We need reliable means of searching patents and publications so that we know what’s been done, what’s already out there.

Like any company in our position, whether we’re looking at synthesis routes, structure–activity relationships or patents, we need easy access to high-quality data.

What are your main sources for such data?While we do use publically available resources such as PubMed and Google Scholar, Reaxys is our main source for finding synthetic route information and chemical property data, and a major source of patent information. Reaxys is my personal preference for finding chemistry data.

“Our resources are limited so we want to achieve synthesis in as few steps and with as high a yield as possible. It saves us a lot of time and a lot of optimization processes if we can understand the synthetic methods that have been used in the past with similar classes of compound—that historical data and all those published experimental procedures really inform our planning.”– Dr. Fabio Tucci, co-founder of

Epigen Biosciences

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Why do you prefer Reaxys?I find Reaxys very intuitive. It covers most of the literature for what we’re doing in terms of synthetic chemistry, medicinal chemistry and bioactivity. The data quality is excellent and the way the data is presented in the interface makes it very easy to work with. Reaxys has that perfect balance of a strong database and an intuitive interface.

What are the challenges that you encounter in data retrieval and management?A major challenge is certainly that the data format can vary considerably, having come from various types of assay. That can make it difficult to compare. If you’re a medicinal chemist working on structure–activity relationships for hit-to-lead or lead optimization, you need

consistent information about the assay parameters for literature compounds so that you can make proper comparisons with reference compounds and assays. It takes a lot of time to normalize data.

And of course there’s the volume of data. We sometimes have to scour multiple papers and read entire patents to find the data that’s buried in them.

Those are areas where Reaxys comes into play. It enables us to find answers faster because the data and experimental procedures have been extracted—we don’t have to read full papers. Also, Reaxys makes computational work easier because the chemical and bioactivity data are normalized. We don’t have to perform the normalization ourselves.

“ I find Reaxys very intuitive. It covers most of the literature for what we’re doing in terms of synthetic chemistry, medicinal chemistry and bioactivity.”

– Dr. Fabio Tucci, co-founder of Epigen Biosciences

The co-founders of Epigen Biosciences

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At what stages of your work is Reaxys most useful?We use Reaxys intensively for hit identification, hit-to-lead and lead optimization. For idea generation, we typically scour the biological literature so we don’t reference Reaxys as much. And when we get to preclinical efficacy and safety testing there are other types of literature that are more relevant. But across these three stages, Reaxys is our main resource.

Naturally, we use it somewhat differently at each stage. For hit identification, we search for information on chemical compounds that affect the receptor of interest and related receptors. We also look at patentability of the hits and analogues of interest. We need to look for compounds that have been synthesized or predicted in that chemical space.

In hit-to-lead, synthetic routes are more important to us. We look at synthetic methods for the hit and all its analogs and ideally want to find a robust method that enables parallel synthesis of various analogs.

For lead optimization, our focus is on discrete chemical modifications and their effects, so our focus is on physicochemical properties, efficacy and toxicity profiles and so on. We also want to ensure that our synthetic route for the lead candidate is scalable, meaning that synthetic route information is still a major concern.

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Could you share some of the specifics of a project where data from Reaxys helped to advance your research? The first one that comes to mind is a potential renal fibrosis treatment we’ve been working on. Our research focus was finding antagonists for the LPA1 receptor (Figure 1) because the literature around that particular receptor was very compelling. Thanks to our collaboration with one of the country’s leading nephrology departments at Yale University and a small business grant from the NIH, we were able to delve deeply into the chemistry of compounds that might affect that target, identifying hits and looking at their physicochemical properties, and then synthesizing and optimizing several of those compounds. In vivo testing using mouse models of renal fibrosis revealed very good efficacy.

We’re actually ready to test our optimized leads in more relevant models of kidney disease.

In finding hits and in the hit-to-lead design, Reaxys was a major resource to look at what other molecules were being worked on by other people. Based on those data, we could make our own designs. We primarily used Reaxys to look into the most efficient synthetic methodologies for the most promising hits and to inform our lead optimization choices.

Reaxys was certainly the right tool for our data needs. We’re at a very exciting stage with our development and we’re extremely pleased with how it has gone so far.

LPA1

Gα12/13 Gαq/11 Gαi/o

Rho

ROCK SRF IP3 DAG

Ca2+ PKC

MAPK AKT Rac

PLC Ras PI3K

Figure 1. The signalling pathways activated by the LPA1 receptor.

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we use reaxys intensively for hit identification, hit-to ... · 2 case study dr. fabio c. tucci,...

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