Daily News

Characterizing emerging companies in computational drug development

Abstract

Computation promises to accelerate, de-risk and optimize drug research and development. An increasing number of companies have entered this space, specializing in the design of new algorithms, computing on proprietary data, and/or development of hardware to improve distinct drug pipeline stages. The large number of such companies and their unique strategies and deals have created a highly complex and competitive industry. We comprehensively analyze the companies in this space to highlight trends and opportunities, identifying highly occupied areas of risk and currently underrepresented niches of high value.

This is a preview of subscription content, access via your institution

Access options

/* style specs start */
style{display:none!important}.LiveAreaSection-193358632 *{align-content:stretch;align-items:stretch;align-self:auto;animation-delay:0s;animation-direction:normal;animation-duration:0s;animation-fill-mode:none;animation-iteration-count:1;animation-name:none;animation-play-state:running;animation-timing-function:ease;azimuth:center;backface-visibility:visible;background-attachment:scroll;background-blend-mode:normal;background-clip:borderBox;background-color:transparent;background-image:none;background-origin:paddingBox;background-position:0 0;background-repeat:repeat;background-size:auto auto;block-size:auto;border-block-end-color:currentcolor;border-block-end-style:none;border-block-end-width:medium;border-block-start-color:currentcolor;border-block-start-style:none;border-block-start-width:medium;border-bottom-color:currentcolor;border-bottom-left-radius:0;border-bottom-right-radius:0;border-bottom-style:none;border-bottom-width:medium;border-collapse:separate;border-image-outset:0s;border-image-repeat:stretch;border-image-slice:100%;border-image-source:none;border-image-width:1;border-inline-end-color:currentcolor;border-inline-end-style:none;border-inline-end-width:medium;border-inline-start-color:currentcolor;border-inline-start-style:none;border-inline-start-width:medium;border-left-color:currentcolor;border-left-style:none;border-left-width:medium;border-right-color:currentcolor;border-right-style:none;border-right-width:medium;border-spacing:0;border-top-color:currentcolor;border-top-left-radius:0;border-top-right-radius:0;border-top-style:none;border-top-width:medium;bottom:auto;box-decoration-break:slice;box-shadow:none;box-sizing:border-box;break-after:auto;break-before:auto;break-inside:auto;caption-side:top;caret-color:auto;clear:none;clip:auto;clip-path:none;color:initial;column-count:auto;column-fill:balance;column-gap:normal;column-rule-color:currentcolor;column-rule-style:none;column-rule-width:medium;column-span:none;column-width:auto;content:normal;counter-increment:none;counter-reset:none;cursor:auto;display:inline;empty-cells:show;filter:none;flex-basis:auto;flex-direction:row;flex-grow:0;flex-shrink:1;flex-wrap:nowrap;float:none;font-family:initial;font-feature-settings:normal;font-kerning:auto;font-language-override:normal;font-size:medium;font-size-adjust:none;font-stretch:normal;font-style:normal;font-synthesis:weight style;font-variant:normal;font-variant-alternates:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-variant-position:normal;font-weight:400;grid-auto-columns:auto;grid-auto-flow:row;grid-auto-rows:auto;grid-column-end:auto;grid-column-gap:0;grid-column-start:auto;grid-row-end:auto;grid-row-gap:0;grid-row-start:auto;grid-template-areas:none;grid-template-columns:none;grid-template-rows:none;height:auto;hyphens:manual;image-orientation:0deg;image-rendering:auto;image-resolution:1dppx;ime-mode:auto;inline-size:auto;isolation:auto;justify-content:flexStart;left:auto;letter-spacing:normal;line-break:auto;line-height:normal;list-style-image:none;list-style-position:outside;list-style-type:disc;margin-block-end:0;margin-block-start:0;margin-bottom:0;margin-inline-end:0;margin-inline-start:0;margin-left:0;margin-right:0;margin-top:0;mask-clip:borderBox;mask-composite:add;mask-image:none;mask-mode:matchSource;mask-origin:borderBox;mask-position:0 0;mask-repeat:repeat;mask-size:auto;mask-type:luminance;max-height:none;max-width:none;min-block-size:0;min-height:0;min-inline-size:0;min-width:0;mix-blend-mode:normal;object-fit:fill;object-position:50% 50%;offset-block-end:auto;offset-block-start:auto;offset-inline-end:auto;offset-inline-start:auto;opacity:1;order:0;orphans:2;outline-color:initial;outline-offset:0;outline-style:none;outline-width:medium;overflow:visible;overflow-wrap:normal;overflow-x:visible;overflow-y:visible;padding-block-end:0;padding-block-start:0;padding-bottom:0;padding-inline-end:0;padding-inline-start:0;padding-left:0;padding-right:0;padding-top:0;page-break-after:auto;page-break-before:auto;page-break-inside:auto;perspective:none;perspective-origin:50% 50%;pointer-events:auto;position:static;quotes:initial;resize:none;right:auto;ruby-align:spaceAround;ruby-merge:separate;ruby-position:over;scroll-behavior:auto;scroll-snap-coordinate:none;scroll-snap-destination:0 0;scroll-snap-points-x:none;scroll-snap-points-y:none;scroll-snap-type:none;shape-image-threshold:0;shape-margin:0;shape-outside:none;tab-size:8;table-layout:auto;text-align:initial;text-align-last:auto;text-combine-upright:none;text-decoration-color:currentcolor;text-decoration-line:none;text-decoration-style:solid;text-emphasis-color:currentcolor;text-emphasis-position:over right;text-emphasis-style:none;text-indent:0;text-justify:auto;text-orientation:mixed;text-overflow:clip;text-rendering:auto;text-shadow:none;text-transform:none;text-underline-position:auto;top:auto;touch-action:auto;transform:none;transform-box:borderBox;transform-origin:50% 50%0;transform-style:flat;transition-delay:0s;transition-duration:0s;transition-property:all;transition-timing-function:ease;vertical-align:baseline;visibility:visible;white-space:normal;widows:2;width:auto;will-change:auto;word-break:normal;word-spacing:normal;word-wrap:normal;writing-mode:horizontalTb;z-index:auto;-webkit-appearance:none;-moz-appearance:none;-ms-appearance:none;appearance:none;margin:0}.LiveAreaSection-193358632{width:100%}.LiveAreaSection-193358632 .login-option-buybox{display:block;width:100%;font-size:17px;line-height:30px;color:#222;padding-top:30px;font-family:Harding,Palatino,serif}.LiveAreaSection-193358632 .additional-access-options{display:block;font-weight:700;font-size:17px;line-height:30px;color:#222;font-family:Harding,Palatino,serif}.LiveAreaSection-193358632 .additional-login>li:not(:first-child)::before{transform:translateY(-50%);content:””;height:1rem;position:absolute;top:50%;left:0;border-left:2px solid #999}.LiveAreaSection-193358632 .additional-login>li:not(:first-child){padding-left:10px}.LiveAreaSection-193358632 .additional-login>li{display:inline-block;position:relative;vertical-align:middle;padding-right:10px}.BuyBoxSection-683559780{display:flex;flex-wrap:wrap;flex:1;flex-direction:row-reverse;margin:-30px -15px 0}.BuyBoxSection-683559780 .box-inner{width:100%;height:100%}.BuyBoxSection-683559780 .readcube-buybox{background-color:#f3f3f3;flex-shrink:1;flex-grow:1;flex-basis:255px;background-clip:content-box;padding:0 15px;margin-top:30px}.BuyBoxSection-683559780 .subscribe-buybox{background-color:#f3f3f3;flex-shrink:1;flex-grow:4;flex-basis:300px;background-clip:content-box;padding:0 15px;margin-top:30px}.BuyBoxSection-683559780 .subscribe-buybox-nature-plus{background-color:#f3f3f3;flex-shrink:1;flex-grow:4;flex-basis:100%;background-clip:content-box;padding:0 15px;margin-top:30px}.BuyBoxSection-683559780 .title-readcube,.BuyBoxSection-683559780 .title-buybox{display:block;margin:0;margin-right:10%;margin-left:10%;font-size:24px;line-height:32px;color:#222;padding-top:30px;text-align:center;font-family:Harding,Palatino,serif}.BuyBoxSection-683559780 .title-asia-buybox{display:block;margin:0;margin-right:5%;margin-left:5%;font-size:24px;line-height:32px;color:#222;padding-top:30px;text-align:center;font-family:Harding,Palatino,serif}.BuyBoxSection-683559780 .asia-link{color:#069;cursor:pointer;text-decoration:none;font-size:1.05em;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:1.05em6}.BuyBoxSection-683559780 .access-readcube{display:block;margin:0;margin-right:10%;margin-left:10%;font-size:14px;color:#222;padding-top:10px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .access-asia-buybox{display:block;margin:0;margin-right:5%;margin-left:5%;font-size:14px;color:#222;padding-top:10px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .access-buybox{display:block;margin:0;margin-right:10%;margin-left:10%;font-size:14px;color:#222;opacity:.8px;padding-top:10px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .price-buybox{display:block;font-size:30px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;padding-top:30px;text-align:center}.BuyBoxSection-683559780 .price-buybox-to{display:block;font-size:30px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;text-align:center}.BuyBoxSection-683559780 .price-info-text{font-size:16px;padding-right:10px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif}.BuyBoxSection-683559780 .price-value{font-size:30px;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif}.BuyBoxSection-683559780 .price-per-period{font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif}.BuyBoxSection-683559780 .price-from{font-size:14px;padding-right:10px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .issue-buybox{display:block;font-size:13px;text-align:center;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:19px}.BuyBoxSection-683559780 .no-price-buybox{display:block;font-size:13px;line-height:18px;text-align:center;padding-right:10%;padding-left:10%;padding-bottom:20px;padding-top:30px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif}.BuyBoxSection-683559780 .vat-buybox{display:block;margin-top:5px;margin-right:20%;margin-left:20%;font-size:11px;color:#222;padding-top:10px;padding-bottom:15px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:17px}.BuyBoxSection-683559780 .tax-buybox{display:block;width:100%;color:#222;padding:20px 16px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:NaNpx}.BuyBoxSection-683559780 .button-container{display:flex;padding-right:20px;padding-left:20px;justify-content:center}.BuyBoxSection-683559780 .button-container>*{flex:1px}.BuyBoxSection-683559780 .button-container>a:hover,.Button-505204839:hover,.Button-1078489254:hover,.Button-2496381730:hover{text-decoration:none}.BuyBoxSection-683559780 .readcube-button{background:#fff;margin-top:30px}.BuyBoxSection-683559780 .button-asia{background:#069;border:1px solid #069;border-radius:0;cursor:pointer;display:block;padding:9px;outline:0;text-align:center;text-decoration:none;min-width:80px;margin-top:75px}.BuyBoxSection-683559780 .button-label-asia,.ButtonLabel-3869432492,.ButtonLabel-3296148077,.ButtonLabel-1651148777{display:block;color:#fff;font-size:17px;line-height:20px;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;text-align:center;text-decoration:none;cursor:pointer}.Button-505204839,.Button-1078489254,.Button-2496381730{background:#069;border:1px solid #069;border-radius:0;cursor:pointer;display:block;padding:9px;outline:0;text-align:center;text-decoration:none;min-width:80px;max-width:320px;margin-top:10px}.Button-505204839 .readcube-label,.Button-1078489254 .readcube-label,.Button-2496381730 .readcube-label{color:#069}
/* style specs end */

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Breakdown of computational biotech company/pipeline ownership.
Fig. 2: Company-differentiating positioning and average funding on the basis of drug R&D focus and computational capabilities.
Fig. 3: Timelines of company, deal and funding accumulation.
Fig. 4: Distribution of deal type for computational companies with a drug pipeline.
Fig. 5: Computational biotech deal network analysis.
Fig. 6: Current computational pipeline analysis.

Data availability

The data used for this analysis were retrieved from Cortellis (https://access.clarivate.com/login?app=cortellis) and Crunchbase (https://www.crunchbase.com/). Accounts with these providers are required to access their data. To ensure data availability for the work provided here, the curated data used to generate our figures and analysis are available on GitHub at https://github.com/RekerLab/ComputationalDrugRD and on Zenodo at https://doi.org/10.5281/zenodo.10482006 ref. 32.

Code availability

The code used to generate our figures and analysis are available on GitHub at https://github.com/RekerLab/ComputationalDrugRD and on Zenodo at https://doi.org/10.5281/zenodo.10482006 ref. 32.

References

  1. Brown, N. et al. Artificial intelligence in chemistry and drug design. J. Comput. Aided Mol. Des. 34, 709–715 (2020).

    Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 

  2. Kopp, E. BioXCel Therapeutics announces FDA approval of IGALMI™ (dexmedetomidine) sublingual film for acute treatment of agitation associated with schizophrenia or bipolar I or II disorder in adults. BioXcel Therapeutics (6 April 2022).

  3. Savage, N. Drug discovery companies are customizing ChatGPT: here’s how. Nat. Biotechnol. 41, 585–586 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  4. Joachim, B., Rehm, W., Ryan, S. & Wright, P. A biotech survival kit for a challenging public-market environment. McKinsey (19 September 2022).

  5. Leclerc, O., Suhendra, M. & The, L. What are the biotech investment themes that will shape the industry? McKinsey (10 June 2022).

  6. Hodgson, J. 2022—toughing out the trough. Nat. Biotechnol. 41, 159–173 (2023).

    Article 

    Google Scholar 

  7. Prieto-Martínez, F. D., López-López, E., Juárez-Mercado, K. E. & Medina-Franco, J. L. in In Silico Drug Design (ed. Roy, K.) 19–44 (Academic, 2019).

  8. Mayr, A. et al. Large-scale comparison of machine learning methods for drug target prediction on ChEMBL. Chem. Sci. 9, 5441–5451 (2018).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  9. Zhu, H. Big data and artificial intelligence modeling for drug discovery. Annu. Rev. Pharmacol. Toxicol. 60, 573–589 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  10. Borhani, D. W. & Shaw, D. E. The future of molecular dynamics simulations in drug discovery. J. Comput. Aided Mol. Des. 26, 15–26 (2012).

  11. Modulus discovery closes $20.4M USD Series C. Modulus (1 March 2022).

  12. Jarvis, L. M. Relay Therapeutics launches to tackle protein movement. Chemical & Engineering News (14 September 2016).

  13. Bell, J. Gilead taps into machine learning to find new NASH drugs. BioPharma Dive (16 April 2019).

  14. Chory, E. J., Gretton, D. W., DeBenedictis, E. A. & Esvelt, K. M. Enabling high-throughput biology with flexible open-source automation. Mol. Syst. Biol. 17, e9942 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  15. Ma, C., Peng, Y., Li, H. & Chen, W. Organ-on-a-chip: a new paradigm for drug development. Trends Pharmacol. Sci. 42, 119–133 (2021).

    Article 
    PubMed 

    Google Scholar 

  16. Reker, D. Practical considerations for active machine learning in drug discovery. Drug Discov. Today Technol. 32/33, 73–79 (2019).

    Article 
    PubMed 

    Google Scholar 

  17. Wadman, M. FDA no longer needs to require animal tests before human drug trials. Science 379, 127–128 (2023).

    Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 

  18. Hemmerich, J. & Ecker, G. F. In silico toxicology: from structure–activity relationships towards deep learning and adverse outcome pathways. Wiley Interdiscip. Rev. Comput. Mol. Sci. 10, e1475 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  19. Baig, M. H. et al. Computer aided drug design: successes and limitations. Curr. Pharm. Des. 22, 572–581 (2016).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  20. Bhardwaj, A. et al. Open source drug discovery—a new paradigm of collaborative research in tuberculosis drug development. Tuberculosis 91, 479–486 (2011).

    PubMed 

    Google Scholar 

  21. Weingarten, M. D. E. Shaw Research licenses first-in-class therapeutic for immunological diseases to Lilly. D. E. Shaw Research (13 June 2022).

  22. Hale, C. Schrödinger’s in-house pipeline helps fetch $2.7B molecule discovery deal with BMS. Fierce Biotech (18 January 2020).

  23. Olleros, F.-J. Emerging industries and the burnout of pioneers. J. Prod. Innov. Manag. 3, 5–18 (1986).

    Article 

    Google Scholar 

  24. Pagano, M., Panetta, F. & Zingales, L. Why do companies go public? An empirical analysis. J. Financ. 53, 27–64 (2002).

    Article 

    Google Scholar 

  25. Eboli, M., Ozel, B., Teglio, A. & Toto, A. Connectivity, centralisation and ‘robustness-yet-fragility’ of interbank networks. Ann. Finance 19, 169–200 (2022).

  26. Alexander, C. M. et al. Trends and perspectives of biological drug approvals by the FDA: a review from 2015 to 2021. Biomedicines 10, 2325 (2022).

    Article 

    Google Scholar 

  27. Madura Jayatunga, L. B., Ludwig, R., Schulze, U. & Meier, C. in In Vivo (Pharma Intelligence, 2022).

  28. Lajoie, J. M. & Shusta, E. V. Targeting receptor-mediated transport for delivery of biologics across the blood–brain barrier. Annu. Rev. Pharmacol. Toxicol. 55, 613–631 (2015).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  29. Bender, A. & Cortés-Ciriano, I. Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 1: Ways to make an impact, and why we are not there yet. Drug Discov. Today 26, 511–524 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  30. Eisenstein, M. Active machine learning helps drug hunters tackle biology. Nat. Biotechnol. 38, 512–514 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  31. AlphaFold and beyond. Nat. Methods 20, 163 (2023).

  32. Markey, C. & Croset, S. ComputationalDrugRD. Zenodo https://doi.org/10.5281/zenodo.10482006 (2024).

Download references

Acknowledgements

This work was supported by the Duke Science and Technology Initiative and the NIH NIGMS grant R35GM151255 (D.R.). C.M. is supported by a Pratt Gardner Fellowship from the Duke Biomedical Engineering Department and by the NIH NIGMS Pharmacological Sciences Training Grant NIH T32 GM133352-4.

Author information

Author notes

  1. These authors contributed equally: Chloe Markey, Samuel Croset.

Authors and Affiliations

  1. Department of Biomedical Engineering, Duke University, Durham, NC, USA

    Chloe Markey & Daniel Reker

  2. Bellevue Asset Management, Zurich, Switzerland

    Samuel Croset, Olivia Ruth Woolley, Can Martin Buldun, Christian Koch & Daniel Koller

Authors

  1. Chloe Markey
    View author publications

    You can also search for this author in
    PubMed Google Scholar

  2. Samuel Croset
    View author publications

    You can also search for this author in
    PubMed Google Scholar

  3. Olivia Ruth Woolley
    View author publications

    You can also search for this author in
    PubMed Google Scholar

  4. Can Martin Buldun
    View author publications

    You can also search for this author in
    PubMed Google Scholar

  5. Christian Koch
    View author publications

    You can also search for this author in
    PubMed Google Scholar

  6. Daniel Koller
    View author publications

    You can also search for this author in
    PubMed Google Scholar

  7. Daniel Reker
    View author publications

    You can also search for this author in
    PubMed Google Scholar

Contributions

C.M., S.C., C.K., D.K. and D.R. conceived the study and designed experiments. C.M. and S.C. conducted experiments. C.M., S.C., O.R.W., C.M.B, C.K., D.K. and D.R. analyzed the data. C.M., S.C., C.K., D.K. and D.R. wrote the manuscript. C.K., D.K. and D.R. supervised the work. All authors have read and approved the submitted version of the manuscript.

Corresponding authors

Correspondence to
Christian Koch, Daniel Koller or Daniel Reker.

Ethics declarations

Competing interests

D.R. acts as a consultant to the pharmaceutical and biotechnology industry, as a scientific mentor for the German Accelerator, and serves on the scientific advisory board of Areteia Therapeutics. S.C., O.R.W., C.M.B., C.K. and D.K. are employees of Bellevue Asset Management and members of the investment team BB Biotech, with investments in the biotechnology industry including some of the companies analyzed here—a full list of the portfolio is available at https://www.bbbiotech.ch/ch-en/private/portfolio-strategy/performance-portfolio/our-investments.

Peer review

Peer review information

Nature Computational Science thanks Andreas Bender and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Kaitlin McCardle, in collaboration with the Nature Computational Science team.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Tables 1–3 and Figs. 1–4.

Supplementary Data 1

The companies profiled in this analysis. The sheet shows the company reference list used to conduct the analysis. The data in the value matrix column refer to the type of advantage the company had. The letter indicates the R&D part and the digit the computational advantage. For the R&D component, the indexing is the following: A, modality; B, biology; C, delivery; D, safety; E, clinical; F, regulatory. For the computational advantage, the index is the following: 1, hardware; 2, dataset; 3, algorithm (XLSX 14 kb).

Supplementary Data 2

The projects analyzed in this paper. The sheet shows the most advanced projects in computational drug R&D company pipelines (XLSX 11 kb).

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Markey, C., Croset, S., Woolley, O.R. et al. Characterizing emerging companies in computational drug development.
Nat Comput Sci 4, 96–103 (2024). https://doi.org/10.1038/s43588-024-00594-8

Download citation

  • Received: 03 August 2023

  • Accepted: 12 January 2024

  • Published: 26 February 2024

  • Issue Date: February 2024

  • DOI: https://doi.org/10.1038/s43588-024-00594-8

news

Leave a Reply

Your email address will not be published. Required fields are marked *