Quality-by-Design for Medical Device & Drug Development

  • easyQBD is a service developed by CYBERnano to facilitate the implementation of Quality-by-Design best practices in Bio- and Nano-industry.

  • It helps engineers and researchers to better control quality and safety during all the life cycle of the nanoproducts.

  • It also aims at speeding up the development phase by addressing the critical questions and identifiying the main risk factors as soon as possible.

  • easyQBD embeds a large spectrum of facilities in nanoinformatics, risk assessment, design of experiments, assumption testing, statistical learning and data-driven modeling.

  • The CYBERnano team is composed of biostatisticians, bioinformaticians and biologists to support you during the QbD implementation.

easyQBD offers a package of statistical services to the biopharmaceutical and biotechnology sectors:

  • Design of Experiments

  • Statistical Testing

  • Factorial Analysis

  • Multivariate Regression Studies

  • Clustering Analysis

  • Classification Studies

  • Learning Technologies

  • Time Series Analysis

  • Spectral Analysis

  • Process Analytical Technolgy

  • Process Control Strategy

with applications to:

  • Mammalian Cell Culture

  • Cytotoxicity Studies

  • Anti-Cancer Response Analysis

  • Viral Production

  • Cardiotoxicity Studies (ICH S7B)

  • Bioproduction Optimization

  • In vivo studies

  • Radiosensitivity Tests

  • Physico-Chemical Characterizations of Nanoparticles

Why easyQBD ?

easyQBD is a collaborative web platform of services for physicists, biologists and chemists who wish to be assisted in the development of their molecules, nanoparticles and medical devices in compliance with the FDA & EMA guidance on Quality-by-Design. You are assisted by biostatistians & biologists, experts in QbD, and involved in every stages of QbD implementation.

easyQBD provides you a complete QbD report to facilitate the future regulatory submission of your nano-products.

easyQBD embeds advanced statistical tools for:

  • education documents & support

  • risk analysis, 

  • design of experiments, 

  • data analysis,

  • technical report edition

Use Cases ...

Image de Reproductive Health Supplies Co


QbD for the development of an injectable hydrogel tailored for oral bone defect reconstruction


Magnetic NP

Quality-by-Design applied to the development of Magnetic Nanoparticles for Hyperthermia



Design of Simulated Experiments for the optimization of nanoparticles activated by X-ray in radiotherapy.



Quality-by-Design for a safe development of a biocompatible and flexible synthetic cornea



Quality-by-Design for the safe development of lipid nanoparticles devoted to siRNA delivery



Quality-by-Design for the production optimization of bioprocesses


MD Soft

Quality-by-Design for the risk and robustness analysis of software devoted to medical applications



Quality-by-Design for the safe development of nanocarriers produced by Microfluidics



Quality-by-Design for the risk analysis of a medical device prototype in photodynamic therapy

Our Quality-by-Design cycle:

Our Scientific Expertise :

  • EXPERT, developing an effective off-the-shelf platform-based nanosized delivery system for mRNA and to execute the first-in-man clinical study with this formulation, H2020 SC1-BHC, 2019-2024

  • TBMED, An Open Innovation test bed for the development of high-risk medical devices, H2020 NMBP, 2018-2022

  • M3ODALIty, Modular, Multivalent and Multiplexed tOols for DuAl moLecular Imaging, ANR, 2017-2020

  • NanoBiT, Nanoscintillator‐Porphyrin Complexes for Bimodal RadioPhotoDynamic Therapy, EuroNanoMed II, 2016-2018

  • PhotoBrain, AGuIX theranostic nanoparticles for vascular-targeted interstitial photodynamic therapy of brain tumors, projet, EuroNanoMed II, 2015-2017.

  • Nano-Xrays, Nanoparticles-based X ray-induced photodynamic therapy in glioblastoma multiforme, INCA, 2012-2015

  • PDTX, Active Nanoplatforms for Photodynamic Therapy, ANR-P2N, 2011-2014

  • Target-PDT, Photodynamic Therapy using photosensitizer-doped targeted organic nanoparticles, EuroNanoMed I, 2009-2013

Our References :

  1. Blanka Halamoda-Kenzaoui, Simon Baconnier, Thierry Bastogne, Didier Bazile, Patrick Boisseau, Gerrit Borchard, Sven Even Borgos, Luigi Calzolai, Karin Cederbrant, Gabriella di Felice, Tiziana Di Francesco, Marina Dobrovolskaia, Rogério Gaspar, Belén Gracia, Vincent A. Hack- ley, Lada Leyens, Neill Liptrott, Margriet Park, Anil Patri, Gert Roebben, Matthias Roesslein, René Thurmer, Patricia Urban Lopez, Valérie Zuang, and Susanne Bremer-Hoffmann. Bridging communities in the field of nanomedicine. Regulatory Toxicology and Pharmacology, 2019.

  2. T. Bastogne, Quality-by-design of nano-pharmaceuticals - A state of the art, Nanomedicine: Nanotechnology, Biology, and Medicine, June 2017.

  3. P. Retif, A. Reinhard, H. Paquot, V. Jouan-Hureaux, S. Pinel, and T. Bastogne. Monte carlo simulations to predict the in vitro ranking of radiosensitizing nanoparticles. Int J Nanomed, 2016.

  4. P. Retif, T. Bastogne, and M. Barberi-Heyob. Robustness analysis of a geant4-gate simulator for nano- radiosensitizers characterization. IEEE Transactions on NanoBioscience, 2016.

  5. P. Retif, S. Pinel, M. Toussaint, C. Frochot, R. Chouikrat, T. Bastogne, and M. Barberi-Heyob. Nanoparticles for radiation therapy enhancement: the key parameters. Theranostics, 5(9):1030–1044, 2015.

  6. J.-B. Tylcz, T. Bastogne, H. Benachour, D. Bechet, E. Bullinger, H. Garnier, and M. Barberi-Heyob. A Model-based Pharmacokinetics Characterization Method of Engineered Nanoparticles for Pilot Studies. IEEE Transactions on NanoBioscience, pages Volume:PP , Issue: 99, Apr. 2015.

  7. M. Pernot, N. P. E. Barry, T. Bastogne, C. Frochot, M. Barberi-Heyob, and B. Therrien. Rational design of an arene ruthenium chlorin conjugate for in vivo anticancer activity. Inorganica Chimica Acta, 414:134–140, Apr. 2014.

  8. M. Pernot, T. Bastogne, N. P. E. Barry, B. Therrien, G. Koellensperger, S. Hann, V. Reshetov, and M. Barberi-Heyob. System biology approach for in vivo photodynamic therapy optimization of ruthenium-porphyrin compounds. Journal of Photochemistry and Photobiology B: Biology, 117:80–89, Dec. 2012.

  9. H. Benachour, T. Bastogne, M. Toussaint, Y. Chemli, A. Sève, C. Frochot, F. Lux, O. Tillement, R. Vanderesse, and M. Barberi-Heyob. Real-time monitoring of photocytotoxicity in nanoparticles- based photodynamic therapy: a model-based approach. PLoS ONE, 7(11):e48617, Nov. 2012.

  10. H. Benachour, A. Sève, T. Bastogne, C. Frochot, R. Vanderesse, J. Jasniewski, I. Miladi, C. Billotey, O. Tillement, F. Lux, and M. Barberi-Heyob. Multifunctional peptide-conjugated hybrid silica nanoparticles for photodynamic therapy and MRI. Theranostics, 2(9):889–904, Sept. 2012.

  11. V. Morosini, T. Bastogne, C. Frochot, R. Schneider, A. François, F. Guillemin, and M. Barberi-Heyob. Quantum Dot-folic acid conjugates as potential photosensitizers in photodynamic therapy of cancer. Photochemical and Photobiological Sciences, 10(5):842–851, May 2011.

  12. D. Bechet, L. Tirand, B. Faivre, F. Plénat, C. Bonnet, T. Bastogne, C. Frochot, F. Guillemin, and M. Barberi Heyob. Neuropilin-1 targeting photosensitization-induced early stages of thrombosis via tissue factor release. Pharmaceutical Research / Pharmaceutical Research (Dordrecht), 27(3):468–479, 2010.

  13. L. Tirand, T. Bastogne, D. Bechet, M. Linder, N. Thomas, C. Frochot, F. Guillemin, and M. Barberi-Heyob. Response surface methodology: an extensive potential to optimize photodynamic therapy con- ditions in vivo. International Journal of Radiation Oncology, Biology, Physics, 75(1):244–252, 2009.

  14. J. Gravier, R. Schneider, C. Frochot, T. Bastogne, F. Schmitt, J. Didelon, F. Guillemin, and M. Barberi-Heyob. Improvement of m-THPC-like photosensitizer selectivity with folate-based targeted delivery. Synthesis and in vivo selective delivery study. Journal of Medicinal Chemistry, 51(13):3867–3877, June 2008.