Caution: JavaScript execution is disabled in your browser or for this website. You may not be able to answer all questions in this survey. Please, verify your browser parameters.
AMR Accelerator SIG on ML call for data

The AMR Accelerator Scientific Interest Group in Machine Learning is building a permeability prediction model for Gram-negative bacteria. Membrane permeability is a major barrier to antibiotic efficacy in Gram-negative pathogens. By enabling the in silico pre-selection of compounds with favourable permeability profiles, we aim to reduce time and cost in early-stage drug discovery and gain a better understanding of the underlying determinants of compound uptake.
Please fill out this form, and we will get in touch with you!

Don't hesitate to contact Leonie von Berlin and Frederik Deroose (COMBINE) if you have any questions!

First name
Last name
Email address
Company/Organisation name
Position
Are you involved in the AMR Accelerator?
Unfortunately, this call is exclusive to AMR Accelerator members. We may expand the call to external participants later!
Please subscribe to our newsletter to receive the latest updates. Thank you for your understanding!
Which project(s) are you a member of?
Do you want to join the AMR Accelerator Scientific Interest Group in Machine Learning?
Do you want to sign up for our bi-annual newsletter and be kept up-to-date on the progress made in the nine AMR Accelerator projects?

By registering, you acknowledge and agree that the COMBINE project can use your data for communication purposes only.
If you want to know how the data entered in this registration form will be treated, please consult COMBINE's privacy policy here. If you have any questions about your data usage, contact COMBINE Communication Manager Tolganay Kabdullayeva.

Exit and clear survey
 
Close