Lars Lindbom (1), Jonas Malmborg (2), Paulina Appelkvist (3) and Bart Ploeger (2)
(1) qPharmetra, Ekerö, Sweden (2) DMPK iMed CNSP AstraZeneca R&D Södertälje, Sweden (3) Neuroscience iMed CNSP AstraZeneca R&D Södertälje, Sweden
Objectives: Efficient selection of compounds in discovery/early development requires optimal use of data generated to learn about key drug properties (exposure, safety and efficacy) in order to make rational decisions. A complicating factor is the variety of different studies with different study designs, animal strains, sampling routes and frequency and analytical procedures. Also, with many drug properties still being unknown experiments might not be optimally designed eventuating in differences in the quality/informativeness of the data. This results in considerable variability in the data, which needs to be addressed properly to allow bringing all information under one common denominator. Our objective was to analyze exposure and efficacy data from several centrally active gamma secretase modulators (GSMs) using an integrated approach to address all sources of variability and uncertainty and to present the results in a comprehensive manner to improve the quality of decision making. GSMs are developed to inhibit the formation of Aβ42, a fragment of the amyloid precursor protein, which is hypothesized to play a key role in Alzheimer’s Disease pathology [1].
Methods: Data from PK and efficacy studies for several GSMs were pooled and analyzed using mixed-effects turn-over models linking the inhibition of Aβ42 to the predicted brain and plasma concentration. The data included studies of (plasma and brain) exposure- and time-response of the effect of GSMs on the change in Aβ42 in brain. Dense PK observations in plasma were available for a small set of animals for each compound. For the majority of the animals a single observation of PK and Aβ42 in plasma and brain was available.
Results: The observed plasma and brain distribution of the GSM compounds, which was found to be non-linear for some compounds, in addition to their delayed effect on the Aβ42 concentration in brain were adequately described. Considerable differences were found in both brain distribution and potency, whereas all compounds showed comparable efficacy.
Conclusions: Using an integrated modeling & simulation approach to show the uncertainty in the concentration-effect relationships from different GSMs allowed to quantitatively compare their potency and efficacy. This allowed considering the differences in the quality/informativeness of the available data in the decision which compound to select for further development in an intuitive and comprehensive manner.
References:
[1] Richter L, Munter LM, Ness J, Hildebrand PW, Dasari M, Unterreitmeier S, Bulic B, Beyermann M, Gust R, Reif B, Weggen S, Langosch D, Multhaup G. Amyloid beta 42 peptide (Abeta42)-lowering compounds directly bind to Abeta and interfere with amyloid precursor protein (APP) transmembrane dimerization. Proc Natl Acad Sci USA. 2010;107(33):14597-602.
Reference: PAGE 21 () Abstr 2468 [www.page-meeting.org/?abstract=2468]
Poster: CNS