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Pablo Cabral, Ken Lin, Sherry Lu, Joana Galvao, Suzy El Bader, Maribel Beaumont, Santhosh Satapati, Harish Shankaran, Paul Rearden, Marc Bruder, Alan Whitehead, John Higgins, Jason Cox, Tony Tam, Antonio Cabal, Paul E Carrington; Concurrent quantitation of a small molecule sGC stimulator and cGMP in ocular tissue and plasma for target engagement studies after intravitreal administration. Applicability of a matrix-based approach.. Invest. Ophthalmol. Vis. Sci. 2020;61(7):4623.
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Soluble guanylate cyclase (sGC) and its endogenous ligand Nitric Oxide (NO) are expressed throughout ocular tissue. NO activates sGC leading to the production of the second messenger cyclic guanosine monophosphate (cGMP), which in turns triggers downstream cGMP-dependent signaling pathways. The NO-sGC pathway is involved in intraocular pressure regulation. We developed an assay to provide pharmacokinetic and target engagement data for intravitreal administration of a soluble guanylate cyclase stimulator.
A liquid chromatography tandem mass spectrometry assay was qualified for the concurrent measurement of a small molecule sGC stimulator and its target engagement biomarker, cGMP, in ocular tissues and plasma. A surrogate matrix approach was used in this assay due to limited quantities of blank ocular matrices in a preclinical discovery research setting. The need for a surrogate matrix is further compounded by endogenous levels of biomarker.
We demonstrated appropriate parallelism between the surrogate matrix and the authentic animal matrices (rabbit plasma, vitreous, and retina-choroid). After assay optimization was completed, qualification experiments showed high accuracy, precision, recovery, and stability.
Dose dependent exposure of the sGC stimulator was found in rabbit vitreous, retina-choroid, and plasma. We detected increased levels of cGMP in vitreous humor, but not retina-choroid. Concurrent measurements of both pharmacokinetic and pharmacodynamic analytes resulted in higher throughput data generation and provided improved context for interpreting PK and PD relationships.
This is a 2020 ARVO Annual Meeting abstract.
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