DR. ASHER D SCHACHTER, M.D.
Medical Practice at Longwood Ave, Boston, MA

2007012, May 31, 2007

Feb 17, 2004

10/545198

Terry Strom - Brookline MA, US
Towia Libermann - Chestnut Hill MA, US
Asher Schachter - Needham MA, US

C12Q 1/68

435006000

The present invention features prognostic methods useful in assessing patients who have received a transplant and reagents, optionally packaged as kits or organized as arrays, that can be used to carry out those methods. The inventions are based, in part, on our analysis of gene expression in renal allografts and clinical parameters, such as the age of the donor. The clinical parameters include one or more variables associated with the recipient (e.g., the recipient's age and/or race); one or more variables associated with the graft (e.g., whether the graft is obtained from a living donor or a cadaver and the ischemic time); and variables associated with the donor (e.g., the donor's age and/or race). The genes that can be assessed include those encoding agents that mediate inflammation, immune activation, and cell death (we may refer to these genes below as “inflammatory”, “immune” or “cytoprotective”). Surprisingly, we found that the levels of gene expression could predict the occurrence of DGF, AR, and the quality of later graft function even when analyzed shortly after the transplant was performed (e.g., shortly after vascular anastomosis and tissue reperfusion). We also found that clinical parameters available at the time of transplantation correlate with decreased graft health and can be considered in combination with gene expression to evaluate a patient's risk for an adverse outcome.

2005002, Jan 27, 2005

Jun 30, 2004

10/881322

Asher Schachter - Needham MA, US
Marco Ramoni - Boston MA, US

G01N033/50

702019000

A method for predicting the success of a new chemical entity, including the steps of providing a signal related to the new chemical entity, providing a therapeutic index, providing a conditional probability table, providing a prior probability distribution, providing a prior N, and calculating a posterior probability distribution for the new chemical entity. An apparatus for predicting the success of a new chemical entity including an input for a signal related to the new chemical entity, a therapeutic index, a conditional probability table, a prior probability distribution, a prior N, and a processor calculating a posterior probability distribution for the new chemical entity.