Quality-by-Design of nano-pharmaceuticals - a state of the art

International audiencePharmaceutical Quality-by-Design is a risk-based approach of drug development relying on the understanding of both the product and the process. This state of the art analyzes 24 studies published during the last ten years. A risk modeling of the nanomaterial formulation and manufacturing is firstly presented. After a brief history of the QbD approach, its basic components are recalled in a second part. The most critical material attributes, process parameters, quality variables and measurement technologies are reviewed. Specific deficiencies are also emphasized such as the absence of prior risk assessment, production scale-up, process analytical technology and control strategy. Finally, perspectives and development priorities are drawn to improve the implementation of this integrative approach of quality and safety in nanomedicine

Protein corona characterization through analytical quality-by-design

Présentation PosterNational audienceAfter administration of nanoparticles (NP) into biological fluids, the NP may interact with surrounding biomolecules like proteins. Those interactions can then cause protein corona (PC) that affect the physicochemical and biological properties of NP. Numerous studies have been carried out to characterize PC effects in simple and complex biological media but our understanding is far from being complete. Moreover, the variety of methods and tools used for this purpose prevents any robust conclusion and sometimes introduces confusions and uncertainty. Analytical Quality by Design (AQbD), introduced in 2010, is the application of the QbD concept, strongly recommended by FDA, to analytical method development. AQbD aims at optimizing accuracy and robustness of analysis results by identifying and controlling critical quality variables and risk factors over the complete protocol, including biological sample preparation, metrological protocol and statistical analysis

A contribution in nanoinformatics to facilitate the collection of structured data for Quality-by-Design in nanomedicine

International audienceBackground. The complexity of nanomaterials, their physico-chemical properties and their interactions with biological and environmental systems, leads to uncertainty in the applicability of experimental data for regulatory purposes that demand sound scientific answers [1]. A major challenge is the establishment of common languages, standards and harmonised infrastructures with applicability to the needs of the different stakeholders. Nanoinformatics is the science and practice of determining which information is relevant to compare characterization of nanomaterials and to design optimized and safe nanodevices. Objectives. Our goal is to bring a new contribution in nanoinformatics by proposing a text mining solution for the quasi-automatic collection of nanomaterials descriptors suited to the preparation of Quality-by-Design studies [2]. Methods. The first step relies on the construction of a non-structured database composed of selected scientific articles in PDF format. Secondly, the Quality-by-Design (ICH Q8-Q11) terminology is used to represent the main descriptors of nanomaterials with three main categories: (i) Critical Quality Attributes to describe the key physical, chemical and biological properties, (ii) Critical Material Attributes and (iii) Critical Process Parameters to characterize both design and manufacturing key variables. In a third step, a text mining algorithm, implemented in the Python language, is used to automatically detect CQA, CMA and CPP in articles and to build up a SQL database. A data curation step is then performed to complete and clean up the QbD database. The proposed approach was applied to a set of 30 scientific articles in Nanomedicine and performances in terms of sensitivity and specificity were finally assessed.Results. In total, 1740 words were automatically analyzed, and we obtained an average response of 83,9% (1459/1740) correct identifications, decomposed as follows: 82,2% (235/286) of accuracy for the CQA descriptors, 92,9% (604/648) for CPP and 76,9% (620/806) for CMA.Conclusion. The proposed nanoinformatic solution has shown promising performances and allows to automate a very time-consuming task related to the collection and analysis of relevant scientific data for risk assessment in Quality-by-Design studies. Short-term perspectives will be focused to the automatic extraction of more complex descriptors

An extension of the target theory in biology applied to system reliability

International audienceWe consider rough products produced by a factory. Each product coming from the plant has m vital elements and some elements can be damaged. To obtain a perfect product (i.e. all the constitutive m elements are safe) all the damaged elements are repaired and a test phase follows. The result of this two-steps procedure is random. We suppose that the number Zk of non-damaged elements is a Markov chain valued in the set {0,1,...,m}, where k is the number of applied repairing-test phases. We have a qualitative result which says that if the repair phase is efficient then P(Zk=m) is close to 1. As for production of a large number n of products, the former result allows us to give conditions under which either the n elements or a fraction of these n elements are (is) safe after the application of k previous maintenance phases

Robust estimation of field potential duration in multi-electrode array signals

Présentation PosterInternational audienceElectrical signals measured by microelectrode arrays (MEAs) allow non-invasive long-term monitoring of cardiomyocyte cultures. However, variability of local responses between electrodes and noise makes difficult the accurate estimation of the field potential duration (FPD). False peaks are often detected and falsify the FDP estimated value, which finally requires for the user to perform some manual corrections for each well. This drawback not only slows down the analysis but also introduces arbitrary estimations and inter-individual errors. The main objective is to develop a new estimation method of FPD taking advantages of all the information contained in the signals measured by all the electrodes of the same well. The motivations are to automatically compute FPD and to improve the accuracy and robustness of the estimation compared to existing techniques already implemented in the available technologies

Quality-by-Design for the safe development of medical devices containing nanomaterials. A study case in photodynamic therapy

Présentation PosterInternational audienceBackground. According to the new medical device regulation (MDR 2017/745), devices employing advanced materials containing nanomaterials will be classified as class III and will have to undergo (re-)assessment of risks. To that aim, the Quality-by-Design approach, as defined in ICH Q8-Q11 (QbD), is indisputably accepted and strongly recommended by the FDA and EMA for risk assessment during drug development. Some papers have emphasized the possible implementation of QbD in the medical device industry [1]. Nevertheless, to date no real and effective adaptation of this risk-based quality management approach has been adapted to biomedical devices manufacturing [2]. Objectives. Our goal is to develop both a new QbD paradigm and a web-based tool devoted to the safe development of class-III medical devices containing nanomaterials. This objective is pursued in the context of the European H2020 project TBMED (An Open Innovation test bed for the development of high-risk medical devices).Methods. A six-step QbD approach is proposed. The first four stages are devoted to the preclinical development while the next two steps concern the industrial implementation. Three categories of risk-assessment methods are used at different development steps: failure mode and effects analysis based on prior knowledge, statistical designs of experiments and Bayesian inference. To assess its applicability, we applied the integrated QbD approach to the development of a new medical device devoted to the realtime control of light during photodynamic therapy using nanoparticle-based photosensitizers. Results. The new SaaS platform, entitled “Nanologic”, is available at: (www.i-nano.eu). Four key documents for regulatory agencies are established during the preclinical study: the target product profile, the list of critical quality attributes (quality/safety descriptors), the list of critical material attributes and process parameters (risk factors associated with the design and production phases) and the design space: a key concept of risk assessment in QbD.Conclusion. We show how the QbD best practices can be adapted to the development of medical devices containing nanomaterials. Moreover, new questions still have to be investigated such as the solutions to be developed to better predict risks associated with the clinical proof of concept

Tumor growth modeling based on cell and tumor lifespans

International audienceThis paper deals with the lifespan modeling of heterogenous tumors treated by radiotherapy. A bi-scale model describing the cell and tumor lifespans by random variables is proposed. First and second-order moments, as well as the cumulative distribution functions and confidence intervals are expressed for the two lifespans with respect to the model parameters. One interesting result is that the mean value of the tumor lifespan can be approached by a logarithmic function of the initial cancer cell number. Moreover, we show that TCP and NTCP, used in radiotherapy to evaluate, optimize and compare treatment plans, can be derived from the tumor lifespan and the surrounding healthy tissue respectively. Finally, we propose a ROC curve, entitled ECT (Efficiency-Complication Trade-off), suited to the selection by clinicians of the appropriate treatment planning

Short-term effects of ocular 2% dorzolamide, 0.5% timolol or 0.005% latanoprost on the anterior segment architecture in healthy cats: a prospective study.

International audienceDorzolamide 2%, timolol 0.5% and latanoprost 0.005% are widely used in the medical management of glaucoma in humans and pets. In this study, we wanted to evaluate the effect of these three molecules belonging to different hypotensive families on intraocular pressure (IOP) and anterior segment architecture in clinically healthy cats and compare these data with those obtained in a previous study under the same conditions in healthy dogs. In this prospective study 45 cats were included and divided into 3 homogeneous groups. For 7 days eye drops were instilled in the right eye (treated eye), dorzolamide 2% BID for the first group, timolol 0.5% BID for the second group and latanoprost 0.005% SID for the third group. The left (untreated) eye of all these cats constitute a control group useful for the statistical analysis of the data. On D0 and D7, the IOP was measured with Tonovet® and then, a high frequency ultrasound (ultrasound biomicroscopy UBM) was undertaken under general anesthesia. A biostatistical study of the 1440 data was then performed. Statistical test validated the use of the controlateral eye as a control, and the representativeness of a sample of 15 animals per group. At D7, the IOP of healthy cats treated with dorzolamide 2% BID decreased significantly whereas no variation was obtained with instillation of timolol 0.5% and latanoprost 0.005%. According to our protocol, these three hypotensive molecules do not significantly affect the architecture of the anterior segment of the clinically healthy feline eye as in dogs

i-Cellulo: a SaaS platform for the automatic statistical analysis of cell impedance signals

Présentation PosterInternational audienceLabel-free methods such as cell impedance assays are in vitro tests increasingly used in drug development. An indirect difficulty with those technologies is the large amount of kinetic responses to be processed. Our objective is to automate the processing and analysis of those data with a web computational server available to all biologists and able to perform multivariate tests, response profile clustering and dynamic AC50 estimation. The proposed solution relies on a SaaS platform in which R-language algorithms have been implemented for the on-line processing of cell impedance signals. Three generic statistical problems are addressed: clustering of response profiles to screen compounds, multivariate testing to compare their activity and AC50 estimation to determine their concentration effects. ANOVA, Kruskall-Wallis and Tuckey’s range tests have been implemented for the multivariate testing. Hierarchical clustering based on Singular Spectrum Analysis were used for the non-supervised response profile classification. A Hill’s model structure and a maximum likelihood estimator were adopted for the AC50 calculation. Hundreds of tests were carried out on real in vitro signals to assess the practical relevance of i-Cellulo for the fast analysis and characterization of anti-cancer activities in early steps of drug development. Results clearly show the ability of this web-based solution to correctly discriminate, classify, compare and rank the anti-cancer responses of tested compounds compared to gold standards. With the advent of real-time cell measurement technologies in preclinical tests, new services for the analysis of high-content data are needed. i–Cellulo is a solution to that challenge and allows biologists to speed up their data analysis and facilitate interpretation of their results