data. In addition he provided analyses of very large libraries of tuberculosis data which highlight important physicochemical properties,. Ekins has highlighted gaps in TB research, specifically in how cheminformatics and other computational tools could be integrated to improve efficiency and provided examples of how computational methods can be used to assist in screening for compounds active against TB In February 2011 Ekins began participating in the MM4TB project as part of Collaborative Drug Discovery. led by Professor Stewart Cole. Science Mobile Applications Ekins co-developed a Wiki with Antony John Williams called Science Mobile Applications launched 21 June 2011. Initially this grew out of a desire to track chemistry Apps (for a paper submitted) and then Apps for science in the chemistry classroom. Database quality Using their respective blogs, Ekins and Antony Williams alerted the scientific community within days of the release of the NCGC NPC browser. that there were significant errors in molecule structures. These observations were later published as an editorial in Drug Discovery Today. Collaborations Pharmaceuticals In 2015, Sean founded Collaborations Pharmaceuticals to build upon collaborations and projects that came out of applying using machine learning approaches. The projects involved neglected diseases such as Tuberculosis, Chagas disease and rare diseases such as Batten Disease, Pitt Hopkins Syndrome and others. To date they have obtained 8 orphan drug designations across 5 rare or neglected diseases, and have widely published their results in peer reviewed journals.[SE1] The company has obtained over $7.6M of funding from NIH and DOD grants to date. Ebola Research Since 2014 Sean has worked on Ebola drug discovery publishing 19 articles. One of these was the first use of a machine learning model to identify compounds active against Ebola (here). [SE2] This identified three active compounds (tilorone, quinacrine and pyronaridine) in vitro which have been subsequently tested in vivo and found to be active in mouse (Articles 1,2,3) (Most recently pyronaridine was shown to have some in vivo activity against Ebola in a Guinea pig. These molecules have also shown activity against Marburg, and bind the Ebola glycoprotein. Chagas Disease Research In 2015 Sean developed a machine learning model to predict molecules with activity against T.Cruzi, the parasite which cause Chagas Disease. Pyronaridine was one of several molecules identified with in vitro and in vivo activity. SARS-CoV-2 Research In 2020 the three molecules identified with activity against Ebola were tested against SARS-CoV-2 and were of potential