@inbook {9067,
	title = {The Diagnostic Success Story: C-CAMP COVID-19 Innovations Deployment Accelerator (C-CIDA)},
	booktitle = {At War with the Single Strand: How Indian Science Fought the COVID-19 Pandemic},
	year = {2025},
	pages = {53{\textendash}56},
	publisher = {Springer Nature Singapore},
	organization = {Springer Nature Singapore},
	address = {Singapore},
	abstract = {<p>Novel coronavirus COVID-19 emerged as one of the gravest public healthcare challenges in recent history. Even before the first lockdown started, we at C-CAMP had already felt the need to identify and work with such indigenously developed and indigenously produced COVID-19 innovations for rapid deployment. One of the first such innovations we fast-tracked in early March was a rapid diagnostics kit that has since received regulatory nods and was deployed in the field. As the virus marched on with no sign of reprieve, we recognized the importance of being more organized and focused in our efforts. Through the last decade or so of India{\textquoteright}s biotech boom, India{\textquoteright}s bio start-ups have been putting forward Made-in-India globally competitive solutions. Now was the time to capitalize on these technologies and align them with unmet needs for rapid deployment at an unprecedented scale.</p>
},
	isbn = {978-981-96-8122-8},
	doi = {10.1007/978-981-96-8122-8_5},
	url = {https://doi.org/10.1007/978-981-96-8122-8_5},
	author = {Saiyed, Taslimarif and Chandavarkar, Nandita and Chakraborty, Debarshini and Janardan, Neelanjana and Alam, Mohammad Atif and Patel, Paresh and Gupta, Preksha and Bhardwaj, Vishal and Wala, Bhavisha and Joshi, Niranjan and Mukherjee, Titash and Vuppala, Kiran and Kiran, Amritanjali and Das, Deboleena Raha and Jain, Neeraj and Kumar, Manoj and Chandran, Subhashini and Rao, Madhusudhana and Joshi, Madhav and Kakkar, Abhishek and Khirani, Sekhar},
	editor = {Swarup, Renu and Padmanaban, Govindarajan and Arora, Narendra Kumar}
}
@article {8708,
	title = {Multiplexed fluorescence and scatter detection with single cell resolution using on-chip fiber optics for droplet microfluidic applications [Discovery to Innovation Accelerator, C-CAMP]},
	journal = {Microsyst Nanoeng},
	volume = {10},
	year = {2024},
	month = {2024},
	pages = {35},
	abstract = {<p>Droplet microfluidics has emerged as a critical component of several high-throughput single-cell analysis techniques in biomedical research and diagnostics. Despite significant progress in the development of individual assays, multiparametric optical sensing of droplets and their encapsulated contents has been challenging. The current approaches, most commonly involving microscopy-based high-speed imaging of droplets, are technically complex and require expensive instrumentation, limiting their widespread adoption. To address these limitations, we developed the OptiDrop platform; this platform is a novel optofluidic setup that leverages the principles of flow cytometry. Our platform enables on-chip detection of the scatter and multiple fluorescence signals from the microfluidic droplets and their contents using optical fibers. The highly customizable on-chip optical fiber-based signal detection system enables simplified, miniaturized, low-cost, multiparametric sensing of optical signals with high sensitivity and single-cell resolution within each droplet. To demonstrate the ability of the OptiDrop platform, we conducted a differential expression analysis of the major histocompatibility complex (MHC) protein in response to IFN stimulation. Our results showed the platform{\textquoteright}s ability to sensitively detect cell surface biomarkers using fluorescently labeled antibodies. Thus, the OptiDrop platform combines the versatility of flow cytometry with the power of droplet microfluidics to provide wide-ranging, scalable optical sensing solutions for research and diagnostics.</p>
},
	issn = {2055-7434},
	doi = {10.1038/s41378-024-00665-w},
	author = {Gupta, Preksha and Mohan, Ambili and Mishra, Apurv and Nair, Atindra and Chowdhury, Neeladri and Balekai, Dhanush and Rai, Kavyashree and Prabhakar, Anil and Saiyed, Taslimarif}
}
