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Gur Pines  - Department of Entomology, Agricultural Research Organization, Volcani Center, P.O.B 15159, Rishon LeZion 7505101, Israel.
 Reilly G Fankhauser -  Department of Dermatology, Oregon Health & Science University, Baird Hall 3225 SW Pavilion Loop, Portland, OR 97239, USA. 
Carrie A Eckert  -  Renewable and Sustainable Energy Institute, University of Colorado Boulder, 027 UCB, Boulder, CO 80309, USA; Biosciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO 80401, USA.

Drug resistance is a major healthcare challenge, resulting in a continuous need to develop new inhibitors. The development of these inhibitors requires an understanding of the mechanisms of resistance for a critical mass of occurrences. Recent genome editing technologies based on high-throughput DNA synthesis and sequencing may help to predict mutations resulting in resistance by testing large mutagenesis libraries. Here we describe the rationale of this approach, with examples and relevance to drug development and resistance in malaria.

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Predicting Drug Resistance Using Deep Mutational Scanning
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Gur Pines  - Department of Entomology, Agricultural Research Organization, Volcani Center, P.O.B 15159, Rishon LeZion 7505101, Israel.
 Reilly G Fankhauser -  Department of Dermatology, Oregon Health & Science University, Baird Hall 3225 SW Pavilion Loop, Portland, OR 97239, USA. 
Carrie A Eckert  -  Renewable and Sustainable Energy Institute, University of Colorado Boulder, 027 UCB, Boulder, CO 80309, USA; Biosciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO 80401, USA.

Predicting Drug Resistance Using Deep Mutational Scanning

Drug resistance is a major healthcare challenge, resulting in a continuous need to develop new inhibitors. The development of these inhibitors requires an understanding of the mechanisms of resistance for a critical mass of occurrences. Recent genome editing technologies based on high-throughput DNA synthesis and sequencing may help to predict mutations resulting in resistance by testing large mutagenesis libraries. Here we describe the rationale of this approach, with examples and relevance to drug development and resistance in malaria.

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