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Published on: February 16, 2011
An interview with Hakim Djaballah, Ph.D. Interview by Vicki Glaser.
1High-Throughput Screening Core Facility, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. djaballh@mskcc.org
Assay and Drug Development Technologies
|October 27, 2010
Summary
Dr. Hakim Djaballah directs Memorial Sloan-Kettering Cancer Center's High-Throughput Screening (HTS) Core Facility, advancing preclinical drug discovery. His expertise spans infectious diseases and oncology target identification, utilizing chemical and RNAi screening.
Area of Science:
- Biochemistry and Biotechnology
- Drug Discovery and Development
- Robotics in Scientific Research
Background:
- Dr. Hakim Djaballah leads the High-Throughput Screening (HTS) Core Facility at Memorial Sloan-Kettering Cancer Center (MSKCC).
- Possesses extensive industrial experience in preclinical drug discovery within pharmaceutical and biotechnology sectors.
- Expertise includes screening antibacterials, antivirals, and antifungals, and identifying therapeutic targets.
Discussion:
- The HTS Core Facility at MSKCC employs both chemical and RNA interference (RNAi) screening methodologies.
- Dr. Djaballah's work contributes to identifying novel drug candidates across diverse therapeutic areas such as oncology, inflammation, and CNS disorders.
- His background includes a B.S. in biochemistry with biotechnology and a Ph.D. in biochemistry.
Key Insights:
- Dr. Djaballah's leadership at MSKCC's HTS Core Facility is pivotal for advancing drug discovery initiatives.
- His interdisciplinary experience bridges academic research and industrial drug development.
- The facility's capabilities support the identification of targets in critical disease areas.
Outlook:
- Continued advancement of drug discovery through innovative HTS and RNAi screening platforms.
- Potential for identifying new therapeutic agents for oncology, infectious diseases, and other major health challenges.
- Integration of robotic technologies enhances screening efficiency and throughput, as recognized by the 2007 Robots and Vision User Recognition Award.
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