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WO2003008530A2 - Technique de determination de l'efficacite therapeutique d'une substance au moyen d'un dispositif de micromesure biometrique et utilisation de cette technique - Google Patents

Technique de determination de l'efficacite therapeutique d'une substance au moyen d'un dispositif de micromesure biometrique et utilisation de cette technique Download PDF

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Publication number
WO2003008530A2
WO2003008530A2 PCT/EP2002/007910 EP0207910W WO03008530A2 WO 2003008530 A2 WO2003008530 A2 WO 2003008530A2 EP 0207910 W EP0207910 W EP 0207910W WO 03008530 A2 WO03008530 A2 WO 03008530A2
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WIPO (PCT)
Prior art keywords
population
biological cells
substance
cells
cell
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Ceased
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PCT/EP2002/007910
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WO2003008530A3 (fr
Inventor
Mirko LÜDDE
Frank Kischkel
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Cellcontrol Biomedical Labs AG
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Cellcontrol Biomedical Labs AG
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Publication date
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Priority to AU2002328905A priority Critical patent/AU2002328905A1/en
Publication of WO2003008530A2 publication Critical patent/WO2003008530A2/fr
Publication of WO2003008530A3 publication Critical patent/WO2003008530A3/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G01N33/575—
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
    • G01N33/5011—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics for testing antineoplastic activity

Definitions

  • This invention is directed to a method for determining the therapeutic effectiveness of substance using a microphysiometer and the use of such method for improving an objective quantitative measure of chemosensitivity.
  • the substance may be a pharmaceutical agent or drug used for the treatment of tumours.
  • Clinical trials may be ideal for providing results which represent an average therapeutic response for an entire group of patients.
  • clinical trials can be carried out to test the effectiveness of chemotherapeutic substances or agents on tumour cells of patients.
  • Such clinical trials then yield the therapeutic responses of the chemotherapeutic agent or substance on the tumour cells of the patients in the group tested.
  • the average of the therapeutic responses obtained is normally calculated and taken as the general therapeutic effectiveness of the substance or agent.
  • patients may in practice respond very differently to the same treatment thereby influencing the therapeutic effectiveness of a substance or drug used for that particular patient.
  • one of the main disadvantages of relying on clinical trials is that these trials do not account for the individual differences in the patient's response to a substance used for treatment.
  • the sensor-chip based diagnostic test described by Metzger et al. involves measuring the response of the cells to drug exposure in terms of the acidification rate ( ⁇ V/s) of the surrounding medium using a microphysiometer. Rate data is measured separately and simultaneously on both, cells exposed to drugs and on controlled cells not exposed to drugs. For extracting the necessary information, the rate data is treated by a standard smoothing technique in order to take into account the usual metabolic effects of cells not exposed to drugs, the (normalised and smooth) acidification rate of drug-exposed cells were divided by the (normalised and smooth) acidification rate of cells not exposed. The time average of the resulting data provided the indicator for the overall affect of the drug treatment.
  • the rate data may be influenced by several factors including the individual profile of the tumour, the mechanism of the drug (i.e. whether it is an anti-metabolite, intercalating drug, inhibitor of a mitosis or alkylating agent) or the magnitude of the measuring instruments accuracy.
  • the mechanism of the drug i.e. whether it is an anti-metabolite, intercalating drug, inhibitor of a mitosis or alkylating agent
  • the magnitude of the measuring instruments accuracy Hence, an exact determination of the therapeutic effectiveness may inevitably depend on the appropriate evaluation of the rate data considering these factors.
  • the present invention provides a method for determining the therapeutic effectiveness of a substance using measurements obtained by means of a microphysiometer.
  • the microphysiometer is a biological assay that allows to observe the cumulative metabolic activity of small populations of living cells as a function of time.
  • Some common microphysiometers are described in articles by Parce et al. "Detection of cell-affecting agents with a silicon biosensor” (Science, 246:243-247, 1989) and Owicki et al. "Biosensors based on the energy metabolims of living cells: The physical chemistry and cell biology of extracellular acidification” (Biosensors and Bioelectronics, 7-4:255-272, 1992).
  • the metabolic activity is measured in terms of the rate of change per time of the extracellular electrochemical potential in units of ⁇ V/s.
  • the potential is dependent on the H + -ion concentration, which in turn is dependent e.g. on the. cell's output of carbonic and lactic acids and the impact of its proton pumps. So the potential observed by the microphysiometer is intimately coupled to the ongoing metabolic processes in the cells. By manipulating the extracellular conditions it is possible to immediately record the cell's metabolic responses.
  • the present invention has the advantage that it is possible to define an objective quantitative measure of chemosensitivity on the basis of the microphysiometer technique.
  • the present invention has the further advantage that application of statistical decay models allows to accurately describe the measurements and provides a natural parameter for estimating the chemosensitivity of the cell population under investigation. This contributes to a more accurate and robust method for determining the therapeutic effectiveness of a substance using a microphysiometer.
  • the impact of a chemotherapeutic substance on the cell population as monitored by the microphysiometer might be of a quite complicated nature.
  • the cell population is obtained from biopsy of a tumour or from a cell clone. In either case, a sample is prepared by a procedure known in the art. Several portions of the resulting cell suspensions then become treated with a chemotherapeutic substance, while some untreated portions serve as a reference.
  • the cell population's size is approximately 10 5 cells.
  • the cells are preferably separated from each other such that only few small heaps of up to approximately 6 cells remain unseparated.
  • the cells are kept in agarose in order to provide a stable extracellular environment.
  • the cells are preferably not grown. Thereby, little or no nutrients are present and no growth factors are supplied.
  • the observation takes approximately 16 hours.
  • the preparation can take approximately 3 hours.
  • the concentration of the therapeutic substance is the pharmacological peak plasma concentration in vivo.
  • the activity measured at time t by the microphysiometer is a linear
  • the survival function S k of a cell k is the function of time giving the probability S k (t) that the cell still lives at the time t.
  • a cell's survival function S k and its indicator function l k are related by
  • E denotes the expectation value (statistical average) in the measure p.
  • S k is not a random variable, as it is an averaged quantity.
  • the first equation ' (3) is by definition of the expectation value
  • the second (4) is by definition of the indicator function
  • the last equation (7) is by definition of the survival function S ⁇
  • the cell's lifetime variables T v ..., T N are assumed to be statistically independent and identically distributed. Biologically this means that a cell's death does not depend on any other cell's death and that all the cells statistically behave in an identical way. In reality this might not be fulfilled completely, in particular when the cells are not completely separated from each other. However, under this assumption a good estimator for the expectation of any cell's indicator function, say cell number 1, is given by the sample mean of the indicator functions of all cells,
  • Equation (9) expresses, under the stated assumptions, the change per time of the extracellular potential by a survival probability distribution of the single cells.
  • Equation (9) indicates that this family actually provides a model for the measured cumulative metabolic activity of the whole cell population.
  • a suitable parameter of the survival function as a quantitative measure of the chemosensitivity of the cells under investigation can be used.
  • a model is used to represent the survival function S.
  • Preferred models are, for example, the Weibull and the Verhulst model.
  • the hazard rate h (with respect to the probability measure p) gives the conditional probability h(t) that a cell will die in the next infinitesimal time interval, given that it has survived up to time t.
  • the decay time is the decay time
  • the P.F. Verhulst survival function also called logistic function, is given by
  • Verhulst function assumes the birth of the cell to be at - ⁇ , that is "far away in the past".
  • Weibull function assumes cell birth at a finite time.
  • Fig.1 Cell activity by time. Vincristine treatment.
  • Fig. 3 Weibull approximation and residual (with rescaled y-axis) for a selected vincristine channel.
  • Fig. 4 Weibull approximation and residual (with rescaled y-axis) for a selected reference channel.
  • Fig. 5 Decay parameters by medium and model. Nine treated and nine untreated samples.
  • the model according to the present invention was checked on an adapted KB cell line (i.e. a human cervix carcinoma type cell line). The sensitivity of these cells against a set of 8 cytostatics was determined. It was shown on. the basis of a proliferation assay and by determining 50% - inhibitory concentrations (IC 50 ) that the cells have the highest sensitivity, i.e. the lowest IC 50 for vicristine (a chemotherapeutic substance).
  • IC 50 50% - inhibitory concentrations
  • a balanced salt solution was used as medium. Glucose 10 mM, NaCI 138 mM, KCI 5 mM, CaCI 2 1.3 mM, MgCI 2 0.5 mM, NaH 2 P0 4 0.23 mM, Na 2 HPO 4 0.77 mM at a pH of 7.3.
  • the microphysiometers used were standard CytosensorTM instruments. Independent experiments showed that the accuracy and stability of the measured signals were in the range of 1 to 4 MV/s. The 24 samples occupied 3 cytosensors of each 8 measurement chambers.
  • Fig. 1 shows the original together with the smoothed signal from one of the vincristine channels.
  • the accuracy of the measurement can be estimated from the residual, the difference of the original minus the smoothed signal.
  • a signal from a reference channel is shown in Fig. 2.
  • a numerical summary of the data from these channels is provided in Table 1.
  • Table 1 Summary of cell activity [ ⁇ V/s] in two selected channels.
  • the measured data first was smoothed by the OWESS algorithm with a relative smoother span of 1/5.
  • the data was then approximated by the decay models (in different contexts regarded as growth models) ssasymp , ss eibuli and ssfpl respectively, using the R system's non-linear least squares algorithm NLS as disclosed by Venables et al. in Modern Applied Statistics with S-PLUS. Springer, 2000. 3 rd edition, 2 nd printing.
  • Figs 1 and 2 show the approximated activities and the residuals for the two selected channels.
  • the Verhulst approximations do no reveal much visible difference to the Weibull model.
  • a quantitative measure of the overall quality of the approximations can be given in terms of the residual sum of squared errors (RSS) and of the Akaike information criterion (AIC).
  • the RSS is the sum of squared differences of the approximation minus the signal.
  • the Akaike information criterion is a tradeoff between the quality of fit and the number of parameters needed to achieve the fit. RSS and particularly AIC should not be considered for a single approximation, but rather for comparing different approximations of the same data. Smaller values mean that the approximation is better.
  • the RSS and AIC for the approximations to the smoothed curves are computed, as opposed to the original signals.
  • Table 2 Quality of approximations. 9 treated and 9 untreated samples.
  • Table 3 Decay parameters [s] by medium and model. 9 treated and 9 untreated samples.
  • Table 4 Mann-Whitney-Wilcoxoh test. Alternative hypothesis: difference of decay parameters [s] is smaller than zero. P-value 2.06e-05. 9 treated and 9 untreated samples.
  • the remaining residual data for the Weibull and Verhulst models is in the same order of magnitude as the instrument's inaccuracy. So the residual is likely to be due to technical limitations or environmental influences, and these models are complete within the experimentally prescribed accuracy.
  • the decay parameter of the treated population minus that of the reference population, computed from Weibull or Verhulst model, is a highly significant indicator for the chemosensitivity of the cell population.

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  • Health & Medical Sciences (AREA)
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Abstract

La présente invention concerne une technique de détermination de l'efficacité thérapeutique d'une substance au moyen d'un dispositif de micromesure biométrique. On peut obtenir des résultats plus précis en incorporant un modèle statistique de la survie des cellules tumorales soumises à un traitement par substance chimiothérapeutique. On utilise ce modèle associé à des mesures d'activité métabolique cellulaire obtenues au moyen d'un dispositif de micromesure biométrique de façon à obtenir une technique plus précise et plus robuste pour déterminer l'efficacité thérapeutique d'une substance sur des cellules tumorales. Cette invention concerne aussi l'utilisation de mesure quantitative objective de chimio-sensibilité, de cellules tumorales de préférence.
PCT/EP2002/007910 2001-07-16 2002-07-16 Technique de determination de l'efficacite therapeutique d'une substance au moyen d'un dispositif de micromesure biometrique et utilisation de cette technique Ceased WO2003008530A2 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU2002328905A AU2002328905A1 (en) 2001-07-16 2002-07-16 A method for determining the therapeutic effectiveness of a substance using a microphysiometer and use of the method

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DE10134446.5 2001-07-16
DE10134446 2001-07-16

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WO2003008530A2 true WO2003008530A2 (fr) 2003-01-30
WO2003008530A3 WO2003008530A3 (fr) 2003-08-28

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013188500A1 (fr) * 2012-06-12 2013-12-19 Celcuity, LLC Dosages de cellules entières et méthodes associées
WO2015089380A3 (fr) * 2013-12-12 2015-07-23 Celcuity Llc Tests et procédés pour déterminer la sensibilité d'un sujet individuel à un agent thérapeutique
US11333659B2 (en) 2017-03-20 2022-05-17 Celcuity Inc. Methods of measuring signaling pathway activity for selection of therapeutic agents

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5860917A (en) * 1997-01-15 1999-01-19 Chiron Corporation Method and apparatus for predicting therapeutic outcomes

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013188500A1 (fr) * 2012-06-12 2013-12-19 Celcuity, LLC Dosages de cellules entières et méthodes associées
JP2015527055A (ja) * 2012-06-12 2015-09-17 セルキュイティー， エルエルシー 細胞全体でのアッセイおよび方法
US9404915B2 (en) 2012-06-12 2016-08-02 Celcuity Llc Whole cell assays and methods
US10041934B2 (en) 2012-06-12 2018-08-07 Celcuity Llc Whole cell assays and methods
JP2019022529A (ja) * 2012-06-12 2019-02-14 セルキュイティー インコーポレイテッド 細胞全体でのアッセイおよび方法
JP2021007416A (ja) * 2012-06-12 2021-01-28 セルキュイティー インコーポレイテッド 細胞全体でのアッセイおよび方法
US10976307B2 (en) 2012-06-12 2021-04-13 Celcuity Inc. Whole cell assays and methods
JP7108323B2 (ja) 2012-06-12 2022-07-28 セルキュイティー インコーポレイテッド 細胞全体でのアッセイおよび方法
WO2015089380A3 (fr) * 2013-12-12 2015-07-23 Celcuity Llc Tests et procédés pour déterminer la sensibilité d'un sujet individuel à un agent thérapeutique
US11073509B2 (en) 2013-12-12 2021-07-27 Celcuity Inc. Assays and methods for determining the responsiveness of an individual subject to a therapeutic agent
US11333659B2 (en) 2017-03-20 2022-05-17 Celcuity Inc. Methods of measuring signaling pathway activity for selection of therapeutic agents
US12320799B2 (en) 2017-03-20 2025-06-03 Celcuity Inc. Methods of measuring signaling pathway activity for selection of therapeutic agents

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WO2003008530A3 (fr) 2003-08-28

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