GSGurusingham Sittampalam

Gurusingham Sittampalam

*This is an algorithmically generated author record based on publicly available information.

Gurusingham Sittampalam has a total of 61 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    An approach to rapid distributed manufacturing of broad spectrum anti-viral griffithsin using cell-free systems to mitigate pandemics

    by Shayan G. Borhani, Max Z. Levine, Lauren H. Krumpe, Jennifer Wilson, Curtis J. Henrich, Barry R. O’keefe, Donald Lo, G. Sitta Sittampalam, Alexander G. Godfrey, R. Dwayne Lunsford, et al.

    This study describes the cell-free biomanufacturing of a broad-spectrum antiviral protein, griffithsin (GRFT) such that it can be produced with consistent purity and potency in less than 24 hours. We demonstrate GRFT production using two independent cell-free systems, one plant and one microbial. Griffithsin purity and quality were verified using standard regulatory metrics. Efficacy was demonstrated in vitro against SARS-CoV-2 and HIV-1 and was nearly identical to that of GRFT expressed in vivo . The proposed production process is efficient and can be readily scaled up and deployed anywhere in the world where a viral pathogen might emerge. The current emergence of viral variants has resulted in frequent updating of existing vaccines and loss of efficacy for front-line monoclonal antibody therapies. Proteins such as GRFT with its efficacious and broad virus neutralizing capability provide a compelling pandemic mitigation strategy to promptly suppress viral emergence at the source of an outbreak.


  • Open Access

    Transcriptomic profiling in canines and humans reveals cancer specific gene modules and biological mechanisms common to both species

    by Gregory J. Tawa, John Braisted, David Gerhold, Gurmit Grewal, Christina Mazcko, Matthew Breen, Gurusingham Sittampalam, Amy K. LeBlanc

    Understanding relationships between spontaneous cancer in companion (pet) canines and humans can facilitate biomarker and drug development in both species. Towards this end we developed an experimental-bioinformatic protocol that analyzes canine transcriptomics data in the context of existing human data to evaluate comparative relevance of canine to human cancer. We used this protocol to characterize five canine cancers: melanoma, osteosarcoma, pulmonary carcinoma, B- and T-cell lymphoma, in 60 dogs. We applied an unsupervised, iterative clustering method that yielded five co-expression modules and found that each cancer exhibited a unique module expression profile. We constructed cancer models based on the co-expression modules and used the models to successfully classify the canine data. These canine-derived models also successfully classified human tumors representing the same cancers, indicating shared cancer biology between canines and humans. Annotation of the module genes identified cancer specific pathways relevant to cells-of-origin and tumor biology. For example, annotations associated with melanin production (PMEL,GPNMB, andBACE2), synthesis of bone material (COL5A2,COL6A3, andCOL12A1), synthesis of pulmonary surfactant (CTSH,LPCAT1, andNAPSA), ribosomal proteins (RPL8,RPS7, andRPLP0), and epigenetic regulation (EDEM1,PTK2B, andJAK1) were unique to melanoma, osteosarcoma, pulmonary carcinoma, B- and T-cell lymphoma, respectively. In total, 152 biomarker candidates were selected from highly expressing modules for each cancer type. Many of these biomarker candidates are under-explored as drug discovery targets and warrant further study. The demonstrated transferability of classification models from canines to humans enforces the idea that tumor biology, biomarker targets, and associated therapeutics, discovered in canines, may translate to human medicine.


  • Regenerative Pharmacology

    by George J. Christ, Karl-Erik Andersson, Anthony Atala, Atta Behfar, Timothy A. Bertram, Stefanie Biechler, Peter R. Brink, David Burmeister, Martin K. Childers, Ira S. Cohen, et al.

    Regenerative medicine is broadly defined as the repair or replacement of damaged cells, tissues and organs. It is a multidisciplinary effort in which technologies derive from the fields of cell, developmental and molecular biology; chemical and material sciences (i.e. nanotechnology); engineering; surgery; transplantation; immunology; molecular genetics; physiology; and pharmacology. As regenerative medicine technologies continue to evolve and expand across the boundaries of numerous scientific disciplines, they remain at the forefront of the translational research frontier with the potential to radically alter the treatment of a wide variety of disease and dysfunction. This book will draw attention to the critical role that pharmacological sciences will undeniably play in the advancement of these treatments. This book is invaluable for advanced students, postdoctoral fellows, researchers new to the field of regenerative medicine/tissue engineering, and experienced investigators looking for new research avenues. The first state-of-the-art book in this rapidly evolving field of research.


  • Conceptual and statistical issues in the validation of analytic dilution assays for pharmaceutical applications

    by Wendell C. Smith, G. Sitta Sittampalam

    The discovery research, and development of a pharmaceutical product relies on the availability of validated assays for assessing product characteristics and drug effects in vivo and in vitro. Development of a validated assay is a multifaceted activity that provides many interesting challenges for bioanalytical chemists and statisticians. In paper this the similarity condition for fundamental validity of an analytic dilution assay is reviewed as a basic concept underlying the validation of assays for pharmaceutical applications. The distinction between the validity and the acceptability of an assay is considered in terms of the characteristics evaluated during four stages of validation. Recent guidelines on the validation of analytical procedures published by the U.S. Food and Drug Administration (1,2) are appraised from a statistical perspective and statistical issues in the validation process are discussed.