To Hy-Ternity and beyond. Boris Larchevêque, INDATECH

Transcription

1 To Hy-Ternity and beyond Boris Larchevêque, INDATECH

2 Hello! Are you still thinking that a lonely spectrum can make you see how beautiful we are?

3 A 25 minutes talk Introduction to SRS Industrial point of view Importance of probe s design Increasing distance Equidistant points A few applications on solids Applications to complex liquids (biotech) About acquisition of spatially resolved data 3

4 Introduction to Spatially Resolved Spectroscopy 4

5 NIR Spectroscopy evolution Transmission Spatially Resolved Spectroscopy Reflection 5

6 SRS, a young Idea We now work make it available to manufacturers 6

7 A photon life Some are absorbed Some are scattered Most experience a very dangerous life 7

8 A photon life 10 2 Scattering 1 Absorption Fluo 10-2 Raman 10-6 UV VIS NIR MIR 8 (nm)

9 coefficient value (cm -1 ) A solid process engineer s life let us compare on a pharmaceutical tablet at 1500 nm, 99,5 % of the signal is scattered light nm Source : Time-Resolved NIR Spectroscopy for quantitative analysis of intact pharmaceutical tablets, Christoffer Abrahamsson et al.. From Lund Institute of Technology and Astrazeneca. 9

10 Beer-Lambert Absorption of light depends upon the chemical composition has been modeled by Beer-Lambert A = n i=1 ε λ,i. l. C i What are hoping What we are observing Irradiation by a reference light Transmitted light Irradiation by a reference light Transmitted light Concentration variations Scattered light what is L value??

11 Simulation in Liquid and solid Particle size, shape, density, incident light Mass of the product Density.. Simulations performed with NIRFAST (Darthmouth/Birmingham) 11

12 The theory When liquids and solids are complex in nature, both principles can be applied. This situation was described by Patterson in 1989: R(ρ) = I 0 z 0 exp μ eff ρ 2πρ 2 (μ eff + 1 ρ ) it depends on position, time, absorption, diffusion and boundary conditions This can be resolved by making multi-point measurement. It is called spatially resolved spectrometry (SRS). 12

13 Industrial point of vue 13

14 Some usual questions in Industry What can I measure / which technology is the most efficient to measure this parameter? You are unique and can t totally avoid tests 14 Which type of probe/sensor is best matching my process? Adapting the eye to what you want to see can greatly improve your measurements

15 The probe is the eye When liquids and solids are complex in nature, both principles can be applied. This situation was described by Patterson in 1989: R(ρ) = I 0 z 0 exp μ eff ρ 2πρ 2 (μ eff + 1 ρ ) Thus, spectra depends on position, time, absorption, diffusion and boundary conditions To resolve this, multi-point measurement is necessary. It is called spatially resolved spectrometry (SRS). Example for liquids front view sectional view Example for solids 15

16 For speed, and multipoint hyperspectral imaging is the occipital lobe Fast (millisecond) Up to 30 simultaneous measurement points 400 to 2500 nm Ip65,GMP etc.. 16

17 Increasing distance of measurement

18 Increasing distance Real Time Release on solids standard deviation Filled capsule with homogeneous powder 98 % Filled capsule standard deviation 70 % Filled capsule Filled capsule with inhomogeneous powder 18

19 Increasing distance Real Time Release on solids The monitoring of tablet film coating by NIR spectrometry is possible on an industrial scale process. However, reflection based solutions are limited in terms of spatial distribution and the thickness of the film coating on the tablet surface. With SRS, this problem can be easily solved by measuring several spectra at a growing distance from the light source. As the distance increases, the optical path also increases. This means that the measured spectrum correspond to a light path which has penetrated more deeply into the product, allowing a measurement of a coating film thickness. Light source We measure : Film thickness Moisture gradient in a tablet Homogeneity of the coating To control : Rotation speed Air temperature and volume Spray rate and time Measuring points Coating Tablet 19

20 Equidistant measurement points 20

21 Equidistant measurement points Homogeneity of powders All positions have the same distance. If the sample is homogeneous the spectra must be the same The probe can provide an evaluation of the homogeneity in one single shot (when used with Hy-ternity) Position1 Position2 Position3 21

22 Simple definition of Confidence Limit In flour 6 channels are measured at the same distance 6 x x Raw spectra Normalised spectra Std(normalize(x)) 22

23 Diagnosis of heterogeneity In flour badly mixed with glucose 6 channels are measured at the same distance 7 x x Std(normaliz(x)) Raw spectra Normalised spectra The std of position provides a direct diagnostic of homogeneity 23

24 Heterogeneity Index (at one wavelength) Example of Industrial application heterogeneity index Confidence limit time Blend Blend 3 Blends with Agglomerates 0.05 Blend 1 Blend Blend 0 Unsieved : >0.003% agglomerates 0.02 Blend 0 Sieved (<300µm) Sieved Unsieved Unsieved Unsieved Unsieved Unsieved Very small amount of agglomerates detected in a batch scale Targeted Homogeneous blend 24

25 Some applications to solids 25

26 Examples in pharmaceutics Crystallisation Mean particle size Polymorphism Solvent composition Wet or Dry granulation Moisture content Particle size Polymorphism Density Porosity Drying and freeze-drying Process optimisation and End point detection Crystal attrition Moisture content Homogeneity Blending, extrusion, milling and Mixing Homogeneity Mean particle size Compression Integrity Weight Hardness Thickness friability Coating Moisture Coating thickness Real Time Release API concentration Weight And why not one day dissolution time 26

27 In-line chemistry control of pharmaceutical tablets Prediction with R2 = 0.98 > very close to lab spectrometer > drawback of InGaAs corrected by the multipoint measurement (better view of the variability) > act as repetition > provide the optimal pathlength in the sample HPLC API prediction

28 Detection of cracks 28

29 And now to complex liquids

30 Challenge of complex liquids (Biotech) Many theories on particle characterization For all : Measurements at different angles are necessary The liquids show huge variations : clear to highly turbid, particles in suspension How to understand and control all the information in the system? Illumination Collimated transmission 30

31 RMSEP (%) prediction of biomass in Bacillus subtilis fermentations Source : Suresh N. Thennadil et al., NIR Spectroscopy of Turbid Media: Maximizing Extractable Information Using Light Propagation Theory. Department of Chemical and Process Engineering University of Strathclyde (Glasgow, United Kingdom), Department of Chemical Engineering Qatar University (Doha, Qatar) 0 0,1 0,2 combined (absorption and scattering) 0,3 0,4 0,5 0,6 0,7 0,8 0,9 total diffuse transmittance total diffuse reflectance scattering coefficient collimated transmittance absorption coefficient 1 0,85 0,9 0,95 1 r² The adjacent graph illustrates the performance of models using multiple measurement modes (transmittance, reflectance, absorption, scattering and combined) The approach of decoupling absorption and scattering effects through the use of radiative transfer theory has the potential to effectively remove nonlinear effects due to multiple light scattering which degrade performance of models built for estimating concentrations of analytes.

32 Some examples Using a SAM-Flex Several probes have been used From 3 (0, 90, 180 ) to 15 positions all with embeded temperature sensor 32

33 Aerobic fermentation Pichia Pastoris Mean of Moyenne spectra Position 0 Position 90 Position 180 6mm pathlength nm T=0 Inoculation Simple processing of spectra provide differents information Temps (heures) Ecart-type Standard variation of the spectra Temps (heures) 33

34 prediction of biomass in yeast fermentations The adjacent graph illustrates several cell cultures with different types of yeast. For the five batches, the yeast are inoculated at t0. The blue, purple and black curves show the growth of the biomass until the glucose is depleted. The green and red curves show the effect of a heat which is made at t0+7 hours. The graph below shows the comparison between SRS (in blue) and capacitance (red) systems for the measurement of biomass. SRS is more accurate at low and high concentrations. In both examples, SRS is used to normalise the acquired spectra which enables a robust prediction of biomass production.

35 Each point contains different information Transmission Number of cell -Number of cell Mean part Size (µm)

36 Protocol VIS-NIR spectrometer SAM-Flex probe Multiplexer DART 501 Time t 0 to t 107 t 0 t 107 t 108 to t 230 t 108 t 230 t 231 to t 420 t 231 t 420 addition of yeast 0 g/l of yeast 0 g/l of glucose 10 g/l of yeast 0 g/l of glucose addition of glucose fermentation 10 g/l of yeast 0 g/l of glucose 10 g/l of yeast 200 g/l of glucose 10 g/l of yeast 200 g/l of glucose 14 g/l of yeast 180 g/l of glucose 36

37 Chemometrics Biomass Back scattered signal (0 ) normalised with transmitted signal (180 ) PLS Glucose Transmission (180 ) EPO with two main components (on spectra with yeast and without glucose) PLS Glucose concentration 37

38 Results addition of yeast addition of glucose fermentation Biomass g/l Glucose Concentration g/l 38

39 Conclusion Multipoint imaging combined with SRS technique provide a very efficient tool for solid and liquid PAT applications. Possibility of working at very high speed Prediction of both physical and chemical informations Join us on linkedin SRS ready groupe

40 Thank You very much for your Attention I m sur you will see me differently now.