Nalin Tikoo, MS

Assessment of plasma circulating tumor DNA (ctDNA) level as a prognostic marker for progression-free survival (PFS) following first-line metastatic colorectal cancer (mCRC) therapy.

Molecular biomarkers hold promise for personalization of cancer treatment. However, a typical tumor biopsy may be difficult to acquire and may not capture genetic variations within or across tumors. Given these limitations, tumor genotyping using next-generation sequencing of plasma-derived circulating tumor (ct)-DNA has the potential to transform non–small cell lung cancer (NSCLC) management. Importantly, mutations detected in biopsied tissue must also be detected in plasma-derived ctDNA at… Show more

Molecular biomarkers hold promise for personalization of cancer treatment. However, a typical tumor biopsy may be difficult to acquire and may not capture genetic variations within or across tumors. Given these limitations, tumor genotyping using next-generation sequencing of plasma-derived circulating tumor (ct)-DNA has the potential to transform non–small cell lung cancer (NSCLC) management. Importantly, mutations detected in biopsied tissue must also be detected in plasma-derived ctDNA at different disease stages. Using the AVENIO ctDNA Surveillance kit (research use only), mutations in ctDNA from NSCLC subjects were compared with those identified in matched tumor tissue samples, retrospectively. Plasma and tissue samples were collected from 141 treatment-naïve NSCLC subjects (stage I, n = 48; stage II, n = 37; stage III, n = 33; stage IV, n = 23). In plasma samples, the median numbers of variants per subject were 4, 6, 8, and 9 in those with stage I, II, III, and IV disease, respectively. The corresponding values in tissue samples were 5, 5, 6, and 4. The overall tissue-plasma concordance of stage II through IV was 62.2% by AVENIO software call. On multivariate analysis, concordance was positively and significantly associated with tumor size and cancer stage. Next-generation sequencing–based analyses with the AVENIO ctDNA Surveillance kit could be an alternative approach to detecting genetic variations in plasma-derived ctDNA isolated from NSCLC subjects. Show less

Advances in sequencing technologies have paved the path to better understanding cancer, hereditary diseases, infectious diseases, and prenatal diagnostics. This includes sequencing of germline DNA, tumor tissue DNA, and plasma DNA, i.e. liquid biopsy. Monitoring using plasma DNA compared to traditional imaging based methods has become routine clinical practice thus producing data in gigabyte to terabyte range and resulting in thousands of markers. Visualization and analysis of these data in the… Show more

Advances in sequencing technologies have paved the path to better understanding cancer, hereditary diseases, infectious diseases, and prenatal diagnostics. This includes sequencing of germline DNA, tumor tissue DNA, and plasma DNA, i.e. liquid biopsy. Monitoring using plasma DNA compared to traditional imaging based methods has become routine clinical practice thus producing data in gigabyte to terabyte range and resulting in thousands of markers. Visualization and analysis of these data in the context of clinical data for diagnosis, prognosis, assessment of response to therapy, and outcome measures can be a challenge.Aside from an introduction into the clinical and sequencing data, this paper will present various methods of visualization using SAS® software and R for giving informative views on the complex data. These visualizations serve the purpose of data review and analysis. Code and output snippets will be provided for subject profiling, custom survival analyses, bar charts and an RShiny application. Show less

The 'make' utility is a software engineering tool for managing and maintaining computer programs. It has been used widely in clinical development in the area of statistical programming to manage the creation and maintenance of SAS® programs generating various outputs such as datasets, tables, listings & graphs.

This paper introduces how the creation of descriptor file used by the ‘make’ utility has been automated at BioMarin Pharmaceutical Inc. Details about the descriptor file… Show more

The 'make' utility is a software engineering tool for managing and maintaining computer programs. It has been used widely in clinical development in the area of statistical programming to manage the creation and maintenance of SAS® programs generating various outputs such as datasets, tables, listings & graphs.

This paper introduces how the creation of descriptor file used by the ‘make’ utility has been automated at BioMarin Pharmaceutical Inc. Details about the descriptor file syntax & the SAS program used to create it are described.

I have been working in the pharma/biotech industry in the clinical research area as a statistical programmer analyst. I have gained experience in various aspects of conducting clinical studies like regulatory requirements, and the leading industry practices in statistical programming using SAS®. Show less

Throughout the course of a clinical trial the Statistical Programming group is responsible for the development and management of SAS® programs that generate various outputs such as datasets, tables, listings and graphs. As the clinical development program moves forward these deliverables become increasingly numerous and more challenging to manage. Details about the programs and the project management reports they produce are described in this paper.

I have been working in the… Show more

Throughout the course of a clinical trial the Statistical Programming group is responsible for the development and management of SAS® programs that generate various outputs such as datasets, tables, listings and graphs. As the clinical development program moves forward these deliverables become increasingly numerous and more challenging to manage. Details about the programs and the project management reports they produce are described in this paper.

I have been working in the pharma/biotech industry in the clinical research area as a statistical programmer analyst. I have gained experience in various aspects of conducting clinical studies like regulatory requirements, and the leading industry practices in statistical programming using SAS®. Show less