Emerging Infections and Pharmacodynamics Laboratory

Telephone: (518) 641-6434
Fax: (518) 641-6304
gdrusano@ordwayresearch.org

Research Focus

Dr. Drusano’s main interests are in the area of anti-infective drug effect. He and his team have performed investigations with drugs that affect bacteria, viruses, and fungi. The approach taken by the team is defined by both bench investigations as well as by clinical studies inspired by the bench investigations. In specific, the hollow fiber system allows the performance of Phase I/II clinical trials on the benchtop, allowing identification of the proper drug dose and schedule to achieve the desired endpoint.

The unique aspect to this team’s investigational approach is the combination of the bench data with clinical investigation, all of which is tied together through the use of mathematical modeling techniques. Use of molecular biology to define mechanisms of emergence of resistance in bacteria and mathematical modeling employing 5 parallel inhomogenous differential equations to identify a drug exposure to suppress resistance has been the latest innovation from this group. Other approaches have been the original application of Monte Carlo simulation techniques for target identification and use of stochastic optimal design theory, population pharmacokinetic modeling and MAP-Bayesian estimation to elucidate exposure-response relationships in clinical trials, creating a new paradigm for the design and execution of Phase II dose-finding trials.

Selected Publications

Drusano GL. Antimicrobial Pharmacodynamics: Critical Interactions of 'Bug and Drug'. Nature Reviews: Microbiology. 2004; 4: 289-300.

Jumbe N, A Louie, R Leary, W Liu, MR Deziel, VH Tam, R Bachhawat, C Freeman, JB Kahn, K Bush, M N Dudley, MH Miller, GL Drusano. Application of a mathematical model to prevent in-vivo amplification of antibiotic-resistant bacterial populations during therapy. The Journal of Clinical Investigation 2003; 112: 275-285.

Drusano GL, KHP Moore, JP Kleim, W Prince and A Bye. Rational dose selection for a nonnucleoside reverse transcriptase inhibitor through the use of population pharmacokinetic modeling and Monte Carlo simulation. Antimicrobial Agents and Chemotherapy 2002; 46: 913-916.

Drusano GL, JA Bilello, SL Preston, E Omara, S Kaul, S Schnittman and R Echols. Hollow fiber unit evaluation of a new Human Immunodeficiency Virus (HIV) -1protease inhibitor, BMS 232632, for determination of the linked pharmacodynamic variable. J Infec Dis 2001; 183: 1126-1129.

Drusano GL, JA Bilello, DS Stein, M Nessly, A Meibohm, EA Emini, P Deutsch, J Condra, J Chodakewitz, and DJ Holder. Factors Influencing the Emergence of Resistance to Indinavir: Role of Virologic, Immunologic, and Pharmacologic Variables. J Infect Dis. 1998; 178: 360-367.

Preston SL, Drusano GL, Berman AL, Fowler CL, Chow AT, Dornseif B, Reichl V, Natarajan J, Corrado M. Pharmacodynamics of levofloxacin: a new paradigm for early clinical trials. Journal of the American Medical Association 1998; 279: 125-129.

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