Publications by authors named "François Grand"

8 Publications

  • Page 1 of 1

Multicentre pharmacokinetic evaluation of rFVIII-Fc (efmoroctocog alfa) in a real life and comparison with non-extended half-life FVIII concentrates.

Haemophilia 2020 Mar 27;26(2):282-289. Epub 2020 Feb 27.

Laboratoire d'Hémostase Hémobiologie, CHU de Lille, Lille, France.

The use of enhanced half-life (EHL) FVIII has improved the quality of prophylaxis in haemophilia A, but with a benefit that may vary from one patient to another. We analysed the pharmacokinetic data obtained with efmoroctocog alfa (rFVIII-Fc) in 114 patients and, in 47 cases, compared them to those previously measured with non-EHL FVIII. The in vivo recovery (IVR) of rFVIII-Fc measured with one stage clotting assay (OSA) and chromogenic assay (CSA) was 2.2 and 2.8 IU/mL per IU/kg, respectively. The median half-life (T ) of rFVIII-Fc was 14.5 hours whatever the FVIII:C assay used, but variable and correlated with preinfusion VWF:Ag levels (r = .76). Both IVR and T were lower in patients under 12 years old (2.4 IU/mL per IU/kg and 11.1 hours, respectively; CSA). PK study of rFVIII-Fc vs non-EHL FVIII showed a T ratio of 1.4 in favour of rFVIII-Fc, regardless of the patient's age. However the relative increase in T with rFVIII-Fc was lower than 30% in one-third of patients evaluated, particularly when the previous FVIII administered was a BHK-derived product. This study therefore suggests that analysis of individual PK profile in response to a specific FVIII concentrate is potentially useful before a switch in haemophilia A patients.
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http://dx.doi.org/10.1111/hae.13946DOI Listing
March 2020

Personalized oncology with artificial intelligence: The case of temozolomide.

Artif Intell Med 2019 08 12;99:101693. Epub 2019 Aug 12.

Emlyon Business School, Écully, F-69130, France; ETH Zurich, Zurich, CH-8092, Switzerland. Electronic address:

Purpose: Using artificial intelligence techniques, we compute optimal personalized protocols for temozolomide administration in a population of patients with variability.

Methods: Our optimizations are based on a Pharmacokinetics/Pharmacodynamics (PK/PD) model with population variability for temozolomide, inspired by Faivre et al. [10] and Panetta et al. [25,26]. The patient pharmacokinetic parameters can only be partially observed at admission and are progressively learned by Bayesian inference during treatment. For every patient, we seek to minimize tumor size while avoiding severe toxicity, i.e. maintaining an acceptable toxicity level. The optimization algorithm we rely on borrows from the field of artificial intelligence.

Results: Optimal personalized protocols (OPP) achieve a sizable decrease in tumor size at the population level but also patient-wise. The tumor size is on average 67.2 g lighter than with the standard maximum-tolerated dose protocol (MTD) after 336 days (12 MTD cycles). The corresponding 90% confidence interval for average tumor size reduction amounts to 58.6-82.7 g. When treated with OPP, less patients experience severe toxicity in comparison to MTD.

Major Findings: We quantify in-silico the benefits offered by personalized oncology in the case of temozolomide administration. To do so, we compute optimal personalized protocols for a population of heterogeneous patients using artificial intelligence techniques. At each treatment day, the protocol is updated by taking into account the feedback obtained from patient's reaction to the drug administration. Personalized protocols greatly differ from each other, and from the standard MTD protocol. Benefits of personalization are very sizable: tumor sizes are much smaller on average and also patient-wise, while severe toxicity is made less frequent.
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http://dx.doi.org/10.1016/j.artmed.2019.07.001DOI Listing
August 2019

Optimizing treatment combination for lymphoma using an optimization heuristic.

Math Biosci 2019 09 11;315:108227. Epub 2019 Jul 11.

emlyon business school, Écully F-69130, France; ETH Zurich, Zurich CH-8092, Switzerland.

Background: The standard treatment for high-grade non-Hodgkin lymphoma involves the combination of chemotherapy and immunotherapy. We characterize in-silico the optimal combination protocol that maximizes the overall survival probability. We rely on a pharmacokinetics/pharmacodynamics (PK/PD) model that describes the joint evolution of tumor and effector cells, as well as the effects of both chemotherapy and immunotherapy. The toxicity is taken into account through ad-hoc constraints. We develop an optimization algorithm that belongs to the class of Monte-Carlo tree search algorithms. Our simulations rely on an in-silico population of heterogeneous patients differing with respect to their PK/PD parameters. The optimization objective consists in characterizing the combination protocol that maximizes the overall survival probability of the patient population under consideration.

Results: We compare using in-silico experiments our results to standard protocols and observe a gain in overall survival probabilities that vary from 4 to 9 percentage points. The gains increase with the complexity of the potential protocol. Gains are larger in presence of a higher number of injections or of an actual combination with immunotherapy.

Conclusions: In in-silico experiments, optimal protocols achieve significant gains over standard protocols when considering overall survival probabilities. Our optimization algorithm enables us to efficiently tackle this numerical problem with a large dimensionality. The in-vivo implications of our in-silico results remain to be explored.
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http://dx.doi.org/10.1016/j.mbs.2019.108227DOI Listing
September 2019

Optimizing immune cell therapies with artificial intelligence.

J Theor Biol 2019 01 22;461:34-40. Epub 2018 Oct 22.

Emlyon business school, Écully F-69130, France; ETH Zurich, Zurich CH-8092, Switzerland. Electronic address:

Purpose: We determine an optimal injection pattern for anti-vascular endothelial growth factor (VEGF) and for the combination of anti-VEGF and unlicensed dendritic cells.

Methods: We rely on the mathematical model of Soto-Ortiz and Finley (2016) for the interactions between the tumor growth, angiogenesis and immune system reactions. Our optimization algorithm belongs to the class of Monte-Carlo tree search algorithms. The objective consists in finding the minimal total drug doses for which an injection pattern yields tumor eradication.

Results: Our results are twofold. First, optimized injection protocols enable to significantly reduce the total drug dose for tumor elimination. For instance, for an early diagnosis date, a total dose equal to 58% of the standard anti-VEGF dose enables to eliminate the tumor. In the case of drug combination, associating 25% of the total standard anti-VEGF dose to 10% of the dendritic cell total standard dose eradicates tumor. Our second result is that administering a dose equal to the maximal standard dose allows for later diagnosis date compared to standard protocol. For instance, in the case of anti-VEGF injection, the optimal protocol postpones the maximal diagnosis date by more than one month.

Conclusions: Overall, our optimization based on artificial intelligence delivers significant gains in total drug administration or in the length of the therapeutic window. Our method is flexible and could be adapted to other drug combinations.
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http://dx.doi.org/10.1016/j.jtbi.2018.09.007DOI Listing
January 2019

Optimal dynamic regimens with artificial intelligence: The case of temozolomide.

PLoS One 2018 26;13(6):e0199076. Epub 2018 Jun 26.

emlyon business school, Écully, F-69130, France; ETH Zurich, Zurich, CH-8092, Switzerland.

We determine an optimal protocol for temozolomide using population variability and dynamic optimization techniques inspired by artificial intelligence. We use a Pharmacokinetics/Pharmacodynamics (PK/PD) model based on Faivre and coauthors (Faivre, et al., 2013) for the pharmacokinetics of temozolomide, as well as the pharmacodynamics of its efficacy. For toxicity, which is measured by the nadir of the normalized absolute neutrophil count, we formalize the myelosuppression effect of temozolomide with the physiological model of Panetta and coauthors (Panetta, et al., 2003). We apply the model to a population with variability as given in Panetta and coauthors (Panetta, et al., 2003). Our optimization algorithm is a variant in the class of Monte-Carlo tree search algorithms. We do not impose periodicity constraint on our solution. We set the objective of tumor size minimization while not allowing more severe toxicity levels than the standard Maximum Tolerated Dose (MTD) regimen. The protocol we propose achieves higher efficacy in the sense that -compared to the usual MTD regimen- it divides the tumor size by approximately 7.66 after 336 days -the 95% confidence interval being [7.36-7.97]. The toxicity is similar to MTD. Overall, our protocol, obtained with a very flexible method, gives significant results for the present case of temozolomide and calls for further research mixing operational research or artificial intelligence and clinical research in oncology.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0199076PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6019254PMC
January 2019

Administration of temozolomide: Comparison of conventional and metronomic chemotherapy regimens.

J Theor Biol 2018 06 8;446:71-78. Epub 2018 Mar 8.

Emlyon Business School, Écully F-69130, France; ETH Zurich, Zurich CH-8092, Switzerland. Electronic address:

Purpose: We compare the Maximum Tolerated Dose (MTD) and Metronomic Chemotherapy (MC) protocols for temozolomide administration. We develop an innovative methodology for characterizing optimal chemotherapy regimens.

Methods: We use a PK/PD model based on Faivre et al. (2013) for the pharmacokinetics of temozolomide, as well as the pharmacodynamics of its efficacy. For toxicity, which is measured by the nadir of the normalized absolute neutrophil count, we formalize the myelosuppression effect of temozolomide with the physiological model of Panetta et al. (2003b). We introduce a multi-criteria tool for comparing protocols along their efficacy and toxicity dimensions.

Results: We show that the toxicity of the MC regimen proposed by Faivre et al. (2013) can greatly be reduced without affecting its efficacy, while the standard MTD protocol efficacy cannot be improved without impairing its toxicity. We also show that for any acceptable toxicity level, the optimal protocol remains closely related to standard MTD.

Conclusions: Overall, our new method enables a rich comparison between protocols along multiple dimensions. We can rank protocols for temozolomide administration. It is a first step toward building optimal individual protocols.
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http://dx.doi.org/10.1016/j.jtbi.2018.02.034DOI Listing
June 2018

Age dependency for coagulation parameters in paediatric populations. Results of a multicentre study aimed at defining the age-specific reference ranges.

Thromb Haemost 2016 07 17;116(1):9-16. Epub 2016 Mar 17.

Dr. Pierre Toulon, CHU Nice, Hôpital Pasteur, Service d'Hématologie Biologique, 30, avenue de la Voie Romaine, CS 51069, F-06001 Nice Cedex 1, France, Tel.: + 33 4 92 03 87 09, Fax: + 33 4 92 03 85 95, E-mail:

Understanding of developmental haemostasis is critical to ensure optimal prevention, diagnosis, and treatment of haemorrhagic and thrombotic diseases in children. As coagulation test results are known to be dependent on the reagents/analysers used, it is recommended for each laboratory to define the age-dependent reference ranges by using its own technical condition. That study was carried out in seven centers to establish age-specific reference ranges using the same reagents and analyser. Plasma samples were obtained from 1437 paediatric patients from the following age groups: 15 days-4 weeks (n=36), 1-5 months (n=320), 6-12 months (n=176), 1-5 years (n=507), 6-10 years (n=132) and 11-17 years (n=262). Indication of coagulation testing was pre-operative screening for non-acute diseases in most cases. PT values were similar in the different age groups to those in adults, whereas longer aPTTs were demonstrated in the younger children. Plasma levels of all clotting factors, except for FV, were significantly decreased (p<0.0001) in the youngest children, adult values being usually reached before the end of the first year. The same applied to antithrombin, protein C/S, and plasminogen. In contrast, FVIII and VWF levels were elevated in the youngest children and returned to adult values within six months. The same applied to D-dimer levels, which were found elevated, particularly until six months of life, until puberty. These data suggest that most coagulation test results are highly dependent on age, mainly during the first year of life, and that age-specific reference ranges must be used to ensure proper evaluation of coagulation in children.
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http://dx.doi.org/10.1160/TH15-12-0964DOI Listing
July 2016