Imperial College London

DrJesusRodriguez Manzano

Faculty of MedicineDepartment of Infectious Disease

Senior Lecturer in Diagnostics for Infectious Disease







Commonwealth BuildingHammersmith Campus






Dr. Rodriguez-Manzano and his group are leading the way in developing and implementing innovative methods for molecular diagnosis of infectious diseases and antimicrobial resistance (AMR).

Working at the intersection of hardware, software, and molecular science, the capabilities and technologies we are creating are on the verge of transforming the field of medicine by facilitating swift diagnosis across different environments. This promises to improve clinical outcomes, reduce unnecessary antimicrobial prescribing, and help address the challenges of antimicrobial resistance.

We focus on the most urgent threats as identified by the UK Health Security Agency (with whom we collaborate via the HPRU in HCAI and AMR), the UK Department for Environment, Food & Rural Affairs, and the European Centre for Disease Prevention and Control. These threats include drug-resistant pathogens, respiratory infections (both in humans and animals), febrile illnesses, and skin-tropic viruses. We have a particular interest in ensuring our diagnostic solutions address the challenges of diagnosing diseases in resource-limited settings (publications available on Google Scholar). Current research focuses on the following four Research Lines:

  1. Development and translation of sample-to-result molecular-based diagnostic devices for point-of-care applications (including SmartLidDragonfly and Lacewing diagnostic platforms), to enable the establishment of decentralised health-care systems.
  2. Use of machine learning approaches in combination with PCR-based amplification chemistries (both intercalating dyes and probe-based) to enable accurate high-level multiplexing in conventional real-time instruments and state-of-the art digital PCR platforms, increasing the throughput of diagnostic laboratories without hardware modification.
  3. Development and validation of a novel framework for biomarker discovery to optimise the translation of host-response signatures from high-throughput platforms (e.g., RNAseq and microarray) to PCR-based and point-of-care technologies.
  4. Understanding the fundamental mechanisms of real-time amplification reactions (PCR-based and isothermal chemistries) using single-molecule technologies to enhance analytical and clinical performance.

Dr Rodriguez-Manzano’s group is located at the Centre for Antimicrobial Optimisation (CAMO) within the section of Adult Infectious Disease at Imperial College, Hammersmith campus, bringing together multidisciplinary research on optimising antimicrobial use and infection management. The state-of-the-art laboratories include a data, molecular and mass spectrometry suite, microbiology laboratories, and sensor fabrication facilities.

In response to the COVID-19 pandemic, Dr Rodriguez-Manzano has contributed to national COVID-19 responses through the UK Expert Advisor Science and Technology Committee, and has served as a panelist at the Research and Innovation Forum (GRIF) organised by WHO R&D Blueprint on the theme of “Building the world’s resilience against future outbreaks and pandemics". As a member of the NIHR Health Research Unit in HCAI and AMR, he is actively involved in shaping the UK's plan for tackling AMR.

Dr Rodriguez-Manzano is affiliated with the NIHR Health Protection Research Unit in HCAI and AMR; CAMO-Net Network; Digital Diagnostics for Africa Network; and the Diamonds Consortium.


Dr Jesus Rodriguez-Manzano is the Deputy Director at the Centre for Antimicrobial Optimisation (CAMO) at Imperial and co-founder and Chief Scientific Officer of ProtonDx.

He holds a BSc in Biological Sciences, an MSc in Advanced Microbiology, and a PhD in Microbiology and Biotechnology, all earned from the University of Barcelona in Spain. Following his doctoral studies, he pursued post-doctoral positions in esteemed institutions, including the Division of Chemistry and Chemical Engineering at the California Institute of Technology (Caltech) in the United States and the Department of Electrical and Electronic Engineering at Imperial College London in the United Kingdom. Dr. Rodriguez-Manzano's expertise led him to his current role as a Senior Lecturer (Associate Professor) in the Department of Infectious Disease at Imperial College London, where he contributes to advancing the field of Molecular Diagnostics to tackle infection and antimicrobial resistance.

His academic and professional journey has fostered a strong interdisciplinary background in microbiology, molecular biology, and bioengineering. Dr Rodriguez-Manzano's research interests span various areas, including clinical diagnostics, machine learning applied to healthcare, and single-molecule technologies, with a specific focus on point-of-care applications and low- and middle-income countries.

Dr Rodriguez-Manzano's contributions to the field are evident through his authorship of over 100 scientific publications, including 15 international patent applications. Overall, Jesus Rodriguez Manzano's diverse and accomplished background positions him as a respected authority in the field, with a proven track record of advancing scientific knowledge and contributing to practical solutions in healthcare.

Jesus' research publications can be found in the tab above, or on Google Scholar.

Selected Publications

Journal Articles

Miglietta L, Chen Y, Luo Z, et al., 2023, Smart-Plexer: a breakthrough workflow for hybrid development of multiplex PCR assays., Communications Biology, Vol:6, ISSN:2399-3642

Malpartida-Cardenas K, Baum J, Cunnington A, et al., 2023, A dual paper-based nucleic acid extraction method from blood in under ten minutes for point-of-care diagnostics, Analyst, Vol:148, ISSN:0003-2654, Pages:3036-3044

Jackson HR, Miglietta L, Habgood-Coote D, et al., 2023, Diagnosis of multisystem inflammatory syndrome in children by a whole-blood transcriptional signature, Journal of the Pediatric Infectious Diseases Society, Vol:12, ISSN:2048-7207, Pages:322-331

Malpartida Cardenas K, Moser N, Ansah F, et al., 2023, Sensitive detection of asymptomatic and symptomatic malaria with seven novel parasite-specific LAMP assays and translation for use at point-of-care, Microbiology Spectrum, Vol:11, ISSN:2165-0497, Pages:1-12

Kreitmann L, Miglietta L, Xu K, et al., 2023, Next-generation molecular diagnostics: Leveraging digital technologies to enhance multiplexing in real-time PCR, TRAC-Trends in Analytical Chemistry, Vol:160, ISSN:0165-9936, Pages:1-11

Pennisi I, Moniri A, Miscourides N, et al., 2022, Discrimination of bacterial and viral infection using host-RNA signatures integrated in a lab-on-chip platform, Biosensors & Bioelectronics, Vol:216, ISSN:0956-5663

Miglietta L, Xu K, Chhaya P, et al., 2022, Adaptive filtering framework to remove nonspecific and low-efficiency reactions in multiplex digital PCR based on sigmoidal trends., Analytical Chemistry, Vol:94, ISSN:0003-2700, Pages:14159-14168

Malpartida-Cardenas K, Miglietta L, Peng T, et al., 2022, Single-channel digital LAMP multiplexing using Amplification Curve Analysis, Sensors and Diagnostics, Vol:1, ISSN:2635-0998, Pages:465-468

Li HK, Kaforou M, Rodriguez-Manzano J, et al., 2021, Discovery and validation of a 3-gene signature to distinguish COVID-19 and other viral infections in emergency infectious disease presentations; a case-control then observational cohort study, The Lancet Microbe, Vol:2, ISSN:2666-5247, Pages:594-603

Miglietta L, Moniri A, Pennisi I, et al., 2021, Coupling machine learning and high throughput multiplex digital PCR enables accurate detection of carbapenem-resistant genes in clinical isolates, Frontiers in Molecular Biosciences, Vol:8, ISSN:2296-889X, Pages:1-11

Charani E, McKee M, Ahmad R, et al., 2021, Optimising antimicrobial use in humans-review of current evidence and an interdisciplinary consensus on key priorities for research, The Lancet Regional Health - Europe, Vol:7, ISSN:2666-7762, Pages:1-10

Rodriguez-Manzano J, Malpartida-Cardenas K, Moser N, et al., 2021, Handheld point-of-care system for rapid detection of SARS-CoV-2 extracted RNA in under 20 min, Acs Central Science, Vol:7, ISSN:2374-7943, Pages:307-317

Pennisi I, Rodriguez Manzano J, Moniri A, et al., 2021, Translation of a host blood RNA Signature distinguishing bacterial from viral infection into a platform suitable for development as a point-of-care test, Jama Pediatrics, Vol:175, ISSN:2168-6203, Pages:417-419

Moniri A, Miglietta L, Holmes A, et al., 2020, High-level multiplexing in digital PCR with intercalating dyes by coupling real-time kinetics and melting curve analysis., Analytical Chemistry, Vol:92, ISSN:0003-2700, Pages:14181-14188

Moniri A, Miglietta L, Malpartida Cardenas K, et al., 2020, Amplification curve analysis: Data-driven multiplexing using real-time digital PCR, Analytical Chemistry, Vol:92, ISSN:0003-2700, Pages:13134-13143

Rodriguez Manzano J, Moser N, Malpartida Cardenas K, et al., 2020, Rapid detection of mobilized colistin resistance using a nucleic acid based lab-on-a-chip diagnostic system, Scientific Reports, Vol:10, ISSN:2045-2322

Malpartida-Cardenas K, Miscourides N, Rodriguez-Manzano J, et al., 2019, Quantitative and rapid Plasmodium falciparum malaria diagnosis and artemisinin-resistance detection using a CMOS Lab-on-Chip platform, Biosensors & Bioelectronics, Vol:145, ISSN:0956-5663

Moniri A, Rodriguez-Manzano J, Malpartida-Cardenas K, et al., 2019, Framework for DNA quantification and outlier detection using multidimensional standard curves, Analytical Chemistry, Vol:91, ISSN:0003-2700, Pages:7426-7434

Ming D, Rawson T, Sangkaew S, et al., 2019, Connectivity of rapid-testing diagnostics and surveillance of infectious diseases, Bulletin of the World Health Organization, Vol:97, ISSN:0042-9686, Pages:242-244

Rodriguez-Manzano J, Moniri A, Malpartida-Cardenas K, et al., 2019, Simultaneous single-channel multiplexing and quantification of carbapenem-resistant genes using multidimensional standard curves, Analytical Chemistry, Vol:91, ISSN:0003-2700, Pages:2013-2020

Rodriguez-Manzano J, Karymov MA, Begolo S, et al., 2016, Reading out single-molecule digital RNA and DNA isothermal amplification in nanoliter volumes with unmodified camera phones, ACS Nano, Vol:10, ISSN:1936-0851, Pages:3102-3113

Witters D, Sun B, Begolo S, et al., 2014, Digital biology and chemistry, Lab on a Chip, Vol:14, ISSN:1473-0197, Pages:3225-3232

Sun B, Rodriguez-Manzano J, Selck DA, et al., 2014, Measuring Fate and Rate of Single-Molecule Competition of Amplification and Restriction Digestion, and Its Use for Rapid Genotyping Tested with Hepatitis C Viral RNA, Angewandte Chemie - International Edition, Vol:53, ISSN:1433-7851, Pages:8088-8092


Rodriguez Manzano J, Moniri A, Miglietta L, et al., 2021, Method of assay design

Cavuto M, Pennisi I, Rodriguez Manzano J, et al., 2021, Lid assembly for a sample tube, method of using the same to collect magnetic beads, and sample processing kit

Pennisi I, Rodriguez Manzano J, Miscourides N, et al., 2020, A method for determining a diagnostic outcome

Rodriguez Manzano J, Moniri A, Miglietta L, et al., 2020, Identifying a target nucleic acid

Georgiou P, Moniri A, Rodriguez Manzano J, 2019, A method for analysis of real-time amplification data, GB; WO, WO2019234247A1

Georgiou P, Moniri A, Moser N, et al., 2019, Devices and method for detecting an amplification event, GB; WO, WO2019234451A1

Georgiou P, Malpartida Cardenas K, Yu L-S, et al., 2019, Method for detecting a single nucleotide polymorphism (snp) using lamp and blocking primers, GB; WO, WO2019234251A1

Georgiou P, Yu L-S, Malpartida-Cardenas K, et al., 2019, Method for detecting a tandem repeat, GB; WO, WO2019234252A1

Toumazou C, Baig Mirza K, Rodriguez Manzano J, 2019, Molecule detection using aptamer nucleic acid duplex, GB; WO, WO2019138255A1

Ismagilov RF, Rodriguez Manzano J, Karymov M, et al., 2018, Devices and methods for direct visual detection and readout of single nucleic acid molecules, US WO, WO2017079696A1

Ismagilov, RF, Rodriguez Manzano J, et al., 2017, Enhanced nucleic acid identification and detection, US EP WO, WO2015058008A3

Ismagilov RF, Begolo S, Rodriguez Manzano J, 2016, Devices and Methods for Autonomous Measurements, US; WO, WO2016105508A3

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