US 12,411,128 B2
Methods and apparatuses for prediction of mechanism of activity of compounds
Michelle Khine, Irvine, CA (US); Eugene Lee, Irvine, CA (US); Tang Wai Ronald Adolphus Li, Pok Fu Lam (HK); and David Dan Tran, Aliso Viejo, CA (US)
Assigned to The Regents of the University of California, Oakland, CA (US); and Novoheart International Limited, Hong Kong (CN)
Filed by The Regents of the University of California, Oakland, CA (US); and Novoheart International Limited, Hong Kong (CN)
Filed on Jun. 26, 2018, as Appl. No. 16/019,332.
Claims priority of provisional application 62/525,044, filed on Jun. 26, 2017.
Prior Publication US 2018/0372724 A1, Dec. 27, 2018
Int. Cl. G01N 33/50 (2006.01); G01N 30/86 (2006.01); G01N 33/483 (2006.01); G01N 33/487 (2006.01); G16B 20/00 (2019.01); G16B 40/00 (2019.01); G16B 40/20 (2019.01); G16C 20/00 (2019.01); G16C 20/20 (2019.01); G16C 20/30 (2019.01); G16C 20/40 (2019.01); G16C 20/64 (2019.01); G16C 20/70 (2019.01); G16H 40/00 (2018.01); G16H 50/00 (2018.01)
CPC G01N 33/5061 (2013.01) [G01N 30/8675 (2013.01); G01N 33/4836 (2013.01); G01N 33/48707 (2013.01); G01N 33/48728 (2013.01); G01N 33/48785 (2013.01); G01N 33/48792 (2013.01); G01N 33/5088 (2013.01); G16B 20/00 (2019.02); G16B 40/00 (2019.02); G16B 40/20 (2019.02); G16C 20/00 (2019.02); G16C 20/20 (2019.02); G16C 20/30 (2019.02); G16C 20/40 (2019.02); G16C 20/64 (2019.02); G16C 20/70 (2019.02); G16H 40/00 (2018.01); G16H 50/00 (2018.01)] 19 Claims
OG exemplary drawing
 
1. A platform configured to detect cardioactivity of a drug candidate compound, the platform comprising:
(a) a living cell or a tissue that is capable of exerting a force in response to exposure to the drug candidate compound;
(b) a detector that measures onset, duration and magnitude of the force as a function of time by the living cell or tissue upon exposure to the drug candidate compound;
(c) a memory configured to store data related to the onset, duration and magnitude of the force detected by the detector; and
(d) one or more processing unit(s) configured to:
(i) employ machine learning, wherein a supervised learning algorithm uses a training set to teach one or more model(s) of cardioactivity, allowing the model(s) to learn over time to perform automated drug classification on novel data sets,
(ii) process the data related to the onset, duration and magnitude of the force as a function of time of the living cell or tissue upon exposure to the drug candidate compound,
(iii) consolidate a plurality of parameters pertaining to the onset, duration and magnitude of the force as a function of time into one or more index/indices of cardioactivity, and
(iv) compare the one or more index/indices of cardioactivity to known indices of cardioactivity to determine if the drug candidate compound is capable of modulating cardioactivity,
wherein the platform is configured to apply a plurality of electrical pacing frequencies to the living cell or tissue and wherein cellular response data elicited by the applied plurality of electrical pacing frequencies is captured and analyzed.