Welcome To AGRO

AGRO, a Division of the American Chemical Society, brings together a worldwide community of scientists and stakeholders to advance knowledge and promote innovative solutions for the protection of agricultural productivity, public health, and environment.


Make your plans now to join us in Boston

The next AGRO program will be held in Boston, August 19-23, 2018 at the 256th ACS National Meeting. See the ACS Meetings page for more information.

Abstract submission is now closed. You will receive email notification from ACS when your abstract is accepted and then later provided information on the scheduling of your presentation. The final program will be available in June.

If you have specific questions about the AGRO program, please contact Program Chair, Julie Eble.

The Spring 2018 Issue of the Picogram with Detailed Call for Papers is now available


Lunch and Learn Webinar Series

Co-Sponsored by EAG Laboratories

April 11, 2018
12 noon to 1PM Eastern US Standard Time (5PM GMT)
Moderated by Ken Racke of Dow AgroSciences

“Exposure data quality in environmental epidemiology: 2,4-D as a case study”
Judy LaKind, LaKind Associates, LLC, Cian O’Mahony, Crème Global & Carol Burns, Burns Consulting


Judy LaKind

Carol Burns

Judy S. LaKind, Ph.D. is President of LaKind Associates, LLC, and Adjunct Associate Professor, Department of Epidemiology and Public Health, University of Maryland School of Medicine. She is a health and environmental scientist with expertise in exposure science, assessment of human health risks, biomonitoring, scientific and technical analysis for regulatory support, and state-of-the-science reviews.  Dr. LaKind is also the President of the International Society of Exposure Science.

In general, evaluations of epidemiology studies focus on the consistency of positive (or negative) associations with a specific outcome (i.e. 2,4-D and non-Hodgkin lymphoma).  Checklists and meta-analyses are common tools to aid interpretation of a collection of studies.  Assessing the quality and transparency of the underlying data and harmonizing the exposure and outcome measurements contribute to weight of evidence interpretation of epidemiology data.