Celmatix, Inc.

Medidata Solutions, Inc.

Hrishikesh Karvir

Michael Elashoff

Piraye Yurttas Beim

Jingshu Liu

Christopher Bound

Fanyi Zhang

A system for predicting subject enrollment for a study includes a time-to-first-enrollment (TTFE) model and a first-enrollment-to-last-enrollment (FELE) model for each site in the study. The TTFE model includes a Gaussian distribution with a generalized linear mixed effects model solved with maximum likelihood point estimation or with Bayesian regression, and the FELE model includes a negative binomial distribution with a generalized linear mixed effects model solved with maximum likelihood point estimation or with Bayesian regression estimation.

System and method for predicting subject enrollment

The present invention generally relates to systems and methods for determining the probability of a pregnancy at a selected point in time. Systems and methods of the invention employ an algorithm that has been trained on a reference set of data from a plurality of women for whom at least one of fertility-associated phenotypic traits, fertility-associated medical interventions, or pregnancy outcomes are known, in which the algorithm accounts for any woman who ceases pregnancy attempts prior to reaching a live birth outcome.

Systems and methods for determining the probability of a pregnancy at a selected point in time

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Hamilton, NJ, United States of America

Hrishikesh Karvir