Method and apparatus for performing liquid chromatography purification

Patent metadata

Field	Value
Publication number	US-10620172-B2
Application number	US-201515526506-A
Country	US
Kind code	B2
Filing date	Nov 16, 2015
Priority date	Nov 17, 2014
Publication date	Apr 14, 2020
Grant date	Apr 14, 2020

Abstract

The present invention relates to a method for performing liquid chromatography purification of one or more target molecules from a sample comprising: providing an eluent flow having one or more target molecules, measuring an output parameter indicative of the content of the one or more target molecules in the eluent flow, storing output parameter data, and dividing the eluent flow into consecutive eluent fractions, dividing the output parameter data into corresponding data fractions, in each data fraction obtaining a value indicative of characteristic behavior of the measured output parameter, identifying trends in the measured output parameter based upon the obtained value in consecutive data fractions, and identifying peak(s) in the measured output parameter correlated to eluent fractions based upon the identified trends, whereby information of identified peak(s) and correlated eluent fraction(s) can be presented and purified sample(s) from the eluent may be collected.

First claim

The invention claimed is:

1. A method for performing liquid chromatography purification of one or more target molecules from a sample comprising the steps:
a) performing chromatography purification of the sample providing an eluent flow comprising the one or more target molecules,
b) measuring an output parameter indicative of the content of the one or more target molecules in the eluent flow, storing output parameter data, and
c) dividing the eluent flow into consecutive eluent fractions, and dividing the output parameter data into corresponding data fractions,
wherein said method further comprises the steps:
d) in each data fraction, obtaining a value indicative of characteristic behavior of the measured output parameter in step b),
e) identifying trends in the measured output parameter based upon the obtained value in consecutive data fractions,
f) identifying peak(s) in the measured output parameter correlated to eluent fraction(s) based upon the identified trends,
g) setting an extinction coefficient for each identified peak,
h) setting a target concentration for a molecule with known extinction coefficient,
i) determining peak correlated with the molecule and selecting data fractions within peak to meet the target concentration,
j) presenting molecule concentration and correlated data fractions, and
k) switching between a preparative run and an analytic run in response to the molecule concentration and correlated data fractions.

2. The method according to claim 1 , wherein said value indicative of characteristic behavior is obtained by calculating average output parameter level in each data fraction based on the measured output parameter in step b).

3. The method according to claim 2 , wherein step c) further comprises defining the fraction size of each consecutive eluent fraction.

4. The method according to claim 3 , wherein the eluent fraction size is selected to be predetermined.

5. The method according to claim 3 , wherein eluent fraction size is selected to be dynamic and the method further comprises the steps:
determining trig start position(s) and trig stop position(s) based upon the measured output parameter in step b),
changing the eluent fraction size at each trig start position and restoring the fraction size at each trig stop position,
whereby the amount of each target molecule in each identified peak may be increased.

6. The method according to claim 5 , wherein the eluent fraction size is reduced at each trig start position.

7. The method according to claim 1 , wherein valley(s) are used to identify trends in the measured output parameter, and step e) further comprises determining data fractions being end of peak and determining data fractions being start of new peak to identify each valley.

8. The method according to claim 7 , wherein step b) further comprises determining an integration window, and step e) further comprises the steps:
e1) ensuring that the number of data fractions within the integration window is more than three,
e2) finding derivative signature for each data fraction by comparing an average output parameter level of the data fraction with average output parameter levels of adjacent data fractions, and
e3) using the derivative signature to determine end of peak and start of new peak to identify (trends) each valley.

9. The method according to claim 8 , wherein step e3) further comprises the steps:
identifying end of peak being the preceding data fraction when the average output parameter level of the present data fraction is lower in relation to the average output parameter level of the preceding data fraction and when the average output parameter level of the present data fraction is lower or equal in relation to the average output parameter level of the following data fraction, and
identifying start of new peak being the following data fraction, unless the present data fraction is within a peak, when the average output parameter level of the present data fraction is lower or equal in relation to the average output parameter level of the preceding data fraction and when the average output parameter level of the present data fraction is lower in relation to the following data fraction.

10. The method according to claim 8 , wherein the derivative signature comprises two derivative signs, each derivative sign indicating the relationship between average output parameter level of adjacent data fractions, and step e2) further comprises the steps:
calculating a threshold value for determining a difference in average output parameter level between adjacent data fractions, and
when the difference in average output parameter level is lower than said threshold value, the average output parameter level of two adjacent data fractions is zero, and
when the difference in average output parameter level is higher than said threshold value, the derivative sign is positive if the average output parameter level is higher in following data fraction or the derivative sign is negative if the average output parameter level is lower in following data fraction.

11. The method according to claim 10 , wherein said threshold value is selected to be less than 5% of the difference between the highest and the lowest calculated average output parameter level for the data fractions within said integration window.

12. The method of claim 8 , wherein step f) further comprises the step:
identifying said peak(s) correlated to consecutive data fractions positioned between said start of peak and said end of peak within said integration window.

13. The method of claim 8 , wherein the integration window in step b) is determined by the steps:
b1) setting the integration window to be a default integration window including the output parameter data in step b), and
b2) examining the number of output parameter data points within the integration window.

14. The method according to claim 13 , further comprising
b3) adjusting start of the integration window to coincide with a first event if found, said first event being defined as first injection of the eluent, and
b4) adjusting end of the integration window to include a last event if found, said last event being defined as
last consecutive eluent fraction, or if not found
last output parameter data.

15. The method according to claim 14 , further comprising examining the number of output parameter data points within the integration window, and if less than minimum number of data points the integration window is determined to be the default integration window.

16. The method according to claim 1 , wherein data fraction(s) within a peak with an average output parameter level being less than a predetermined percentage of a maximum average output parameter level of the peak is/are excluded when selecting data fractions to meet target concentration.

17. The method according to claim 16 , wherein the predetermined percentage is selected to be in the range 1-5% of the maximum average output parameter level of the peak.

18. The method of claim 1 , wherein data fraction(s) within a peak with the highest average output parameter level is/are selected first, and data fraction having the lowest average output parameter level or being furthest away from the maximum average output parameter level is selected last to meet the target concentration.

19. The method of claim 18 , further comprising the following step:
g1) presenting peak(s) and correlated eluent fractions of the one or more target molecules, or
g2) presenting content of molecules in peaks based upon the me

Assignees

• Ge Healthcare Bio Sciences Ab

Inventors

• Nyholm Lena
• Hedkvist Lotta
• Arthursson Johan
• Olsson Eva Cecilia
• Larsson Henrik

Classifications

• B01D15/247 Primary

  Fraction collectors · CPC title

• B01D15/10

  characterised by constructional or operational features · CPC title

• G01N30/8644

  Data segmentation, e.g. time windows · CPC title

• G01N30/8631 Primary

  Peaks · CPC title

• G01N30/82

  Automatic means therefor · CPC title