Available Technologies

Browse Penn-owned technologies available for licensing.


Drug discovery and target identification platform technology using random shRNA-expressing library


shRNA library of 3 million sequences for identification of small-RNA therapeutic candidates, new targets and pathways, as well as conventional chemical-compound drugs in cell-culture disease models.  



Robert B. Wilson, MD, PhD


shRNA Drug Discovery



RNA interference (RNAi) using short hairpin RNA (shRNA) is commonly used to inhibit gene expression. shRNA-expressing libraries may have important applications in identifying RNA molecules/sequences with specific biological activity and thus therapeutic implications. Typically, shRNA libraries are limited to sequences that target single mRNAs. Because 7-nucleotide “seed” sequences within shRNAs are sufficient for partial inhibition of target mRNAs, shRNAs are inherently promiscuous. Thus, the single-gene-targeting approach is complicated by off-target effects, which diminish therapeutic indices, and fails to take advantage of multi-gene targeting, which enhances potency. 



To challenge the single-gene-targeting paradigm of small-RNA-based therapeutic initiatives, Dr. Wilson’s lab designed, synthesized, validated, and now further optimized shRNA-expressing libraries that are completely random at the nucleotide level. Three million shRNAs can be screened in a single tissue-culture flask, selecting for the desired phenotype with “hit” sequences retrieved by PCR. Because the libraries are completely random, the screens are unbiased: favorable cell phenotypes reveal which shRNAs are most effective and least toxic. This approach allows identification of sequences that target multiple genes and/or act through non-canonical mechanisms.


Discovery of Drugs, Targets, and Pathways



Traditional drug discovery process involving high-throughput screening is labor-intensive, expensive, often ineffective, and infeasible when cell-culture disease models are unsuitable for microtiter-plate formats.



Random shRNA library screening can be combined with bioinformatic pattern analyses of hit sequences to identify targets, pathways, and conventional chemical-compound therapeutic candidates, bypassing in vivo delivery issues. Thus, each phenotypic screen has the potential to identify, (i) small-RNA therapeutic candidates, (ii) conventional, chemical-compound therapeutic candidates, (iii) target candidates for conventional drug development, and (iv) information on pathways relevant to disease mechanisms.



• Screening, by phenotypic selection, of 3 million shRNAs in a single tissue-culture flask

• Screening for efficacy, and lack of toxicity, simultaneously

• Hit-optimization by random mutagenesis and re-screening

• Translation, using bioinformatics, of gene-expression profiles of “hit” shRNAs to existing drugs

• Inexpensive, simplified, fast method compared to high throughput screening

• Ability to run positive and negative (cancer) screens

• Utilization of  cell-culture disease models unsuitable for microtiter-plate formats



• Identification of shRNA sequences that confer phenotypes of interest or modulate specific biological parameters

• Identification of novel targets, pathways and existing drugs through bioinformatic pattern analyses

• Development of novel therapeutics and biologic tools for a variety of diseases, including, e.g.

• Viral illnesses, by selecting for cell survival in viral cell-culture models

• Cystic Fibrosis, by selecting for increased surface expression of F508del CFTR

• TRAIL-insensitive Malignancies, by selecting for increased surface expression of the TRAIL receptor

• Hypercholesteremia, by selecting for increased surface expression of the LDL receptor

• Parkinson Disease, by selecting for increased expression of PGC1-alpha

• Type II Diabetes, by selecting for protection against inducers of ER stress and the unfolded protein response (UPR) 


Stage of Development

Synthesized, validated, and optimized library of 3 million sequences

Identified shRNAs protecting an IL3-dependent cell line from IL3 withdrawal

Identified shRNAs that reverse phenotypic defects of Friedreich ataxia (FA) fibroblasts

Identified novel targets and existing drugs that reverse phenotypic defects of FA fibroblasts 

Intellectual Property

WO2007103365 (nationalized in US, EU, CA, JP, AU, HK)



Reference Media

Wang et al., PLoS One. 2014; 9(2):e87390

Wang et al., PLoS One. 2008; 3(9):e3171

Cotticelli et al., J Biomol Screen, 2015; 20(9):1084-90



Desired partnerships

• License