Phase 1 dose-escalation, pharmacokinetic, and cerebrospinal fluid distribution study of TAK-285, an investigational inhibitor of EGFR and HER2

Introduction This phase 1 study assessed safety, maximum tolerated dose (MTD), pharmacokinetics, cerebrospinal fluid (CSF) distribution, and preliminary clinical activity of the receptor tyrosine kinase inhibitor TAK-285. Methods Patients with advanced, histologically confirmed solid tumors and Eastern Cooperative Oncology Group performance status ≤2 received daily oral TAK-285; daily dose was escalated within defined cohorts until MTD and recommended phase 2 dose (RP2D) were determined. Eleven patients were enrolled into an RP2D cohort. Blood samples were collected from all cohorts; CSF was collected at pharmacokinetic steady-state from RP2D patients. Tumor responses were assessed every 8 weeks per Response Evaluation Criteria in Solid Tumors. Results Fifty-four patients were enrolled (median age 60; range, 35–76 years). The most common diagnoses were cancers of the colon (28 %), breast (17 %), and pancreas (9 %). Escalation cohorts evaluated doses from 50 mg daily to 500 mg twice daily; the MTD/RP2D was 400 mg twice daily. Dose-limiting toxicities included diarrhea, hypokalemia, and fatigue. Drug absorption was fast (median time of maximum concentration was 2–3 h), and mean half-life was 9 h. Steady-state average unbound CSF concentration (geometric mean 1.54 [range, 0.51–4.27] ng/mL; n = 5) at the RP2D was below the 50 % inhibitory concentration (9.3 ng/mL) for inhibition of tyrosine kinase activity in cells expressing recombinant HER2. Best response was stable disease (12 weeks of nonprogression) in 13 patients. Conclusions TAK-285 was generally well tolerated at the RP2D. Distribution in human CSF was confirmed, but the free concentration of the drug was below that associated with biologically relevant target inhibition

Data from: Phylogenetic inference using discrete characters: performance of ordered and unordered parsimony and of three-item statements

The cladistic literature does not always specify the kind of multistate character treatment that is applied for an analysis. Characters can be treated either as unordered transformation series or as rooted [three-item analysis (3ia)] or unrooted state trees (ordered characters). We aimed to measure the impact of these character treatments on phylogenetic inference. Discrete characters can be represented either as rows or columns in matrices (e.g. for parsimony) or as hierarchies for 3ia. In the present study, we use simulated and empirical examples to assess the relative merits of each method considering both the character treatment and representation. We measure two parameters (resolving power and artefactual resolution) using a new tree comparison metric, ITRI (inter-tree retention index). Our results suggest that the hierarchical character representation not only results (with our simulation settings) in the greatest resolving power, but also in the highest artefactual resolution. Our empirical examples provide equivocal results. Parsimony unordered states yield less resolving power and more artefactual resolutions than parsimony ordered states, both with our simulated and empirical data. Relationships between three operational taxonomic units (OTUs), irrespective of their relationships with other OTUs, are called three-item statements (3is). We compare the intersection tree (which reconstructs a single tree from all of the common 3is of source trees) with the traditional strict consensus and show that the intersection tree retains more of the information contained in the source trees

Grand et al. SOM 1

100 matrices with 8 taxa and 6 characters. These were used in our simulations to test the performance of several methods

Tafuri, Nancy

Character matrix of monilophytes for parsimony analyses with ordered or unordered characters

Grand et al. SOM 6

Resolving power and artifactual resolution rate of the methods (parsimony with unordered and ordered states, and 3ia). Detailed table giving the results for each individual matrix