What they forgot to tell you about machine learning with an application to pharmaceutical manufacturing.

Predictive models (a.k.a.

Analysis of chemometric models applied to Raman spectroscopy for monitoring key metabolites of cell culture.

The Food and Drug Administration (FDA) initiative of Process Analytical Technology (PAT) encourages the monitoring of biopharmaceutical manufacturing processes by innovative solutions. Raman spectroscopy and the chemometric modeling tool partial least squares (PLS) have been applied to this aim for monitoring cell culture process variables. This study compares the chemometric modeling methods of Support Vector Machine radial (SVMr), Random Forests (RF), and Cubist to the commonly used linear PLS model for predicting cell culture components-glucose, lactate, and ammonia.

Automated plaque analysis for the prognostication of major adverse cardiac events.

Objective: The purpose of this study is to assess the value of an automated model-based plaque characterization tool for the prediction of major adverse cardiac events (MACE).

Methods: We retrospectively included 45 patients with suspected coronary artery disease of which 16 (33%) experienced MACE within 12 months. Commercially available plaque quantification software was used to automatically extract quantitative plaque morphology: lumen area, wall area, stenosis percentage, wall thickness, plaque burden, remodeling ratio, calcified area, lipid rich necrotic core (LRNC) area and matrix area.

Validation of Sysmex XT-2000iV analyzer-generated quantitative bone marrow differential counts in cynomolgus monkeys, Beagle dogs, and CD-1 mice.

Background: In a previous study, the validation of rat bone marrow (BM) collection, processing, and analysis using the Sysmex XT-2000iV (Sysmex Corporation, Kobe, Japan) hematology analyzer showed that the Sysmex hematology analyzer produced BM differential counts that were comparable to those obtained with microscopic differential counts.

Objective: This study was conducted to expand the validation of the Sysmex TNCC (total nucleated cell count) and 5-part BM differential in cynomolgus monkeys, Beagle dogs, and CD-1 mice, which are alternate species that are also frequently used in preclinical safety studies.

Methods: The Sysmex 5-part BM differential counts were generated with a two-step process, whereby proliferating and maturing erythroid and myeloid cells were determined by preset gating and lymphocytes were determined using species-specific B- and T-lymphocyte antibodies and a magnetic cell-sorting method (MACS).

Multivariate analysis of cytokine profiles in pregnancy complications.

Problem: The immunoregulation to tolerate the semiallogeneic fetus during pregnancy includes a harmonious dynamic balance between anti- and pro-inflammatory cytokines. Several earlier studies reported significantly different levels and/or ratios of several cytokines in complicated pregnancy as compared to normal pregnancy. However, as cytokines operate in networks with potentially complex interactions, it is also interesting to compare groups with multi-cytokine data sets, with multivariate analysis.

Identification of novel biomarkers to monitor β-cell function and enable early detection of type 2 diabetes risk.

A decline in β-cell function is a prerequisite for the development of type 2 diabetes, yet the level of β-cell function in individuals at risk of the condition is rarely measured. This is due, in part, to the fact that current methods for assessing β-cell function are inaccurate, prone to error, labor-intensive, or affected by glucose-lowering therapy. The aim of the current study was to identify novel circulating biomarkers to monitor β-cell function and to identify individuals at high risk of developing β-cell dysfunction.

Novel Methods for Prioritizing "Close-In" Analogs from Structure-Activity Relationship Matrices.

Here we describe the development of novel methods for compound evaluation and prioritization based on the structure-activity relationship matrix (SARM) framework. The SARM data structure allows automatic and exhaustive extraction of SAR patterns from data sets and their organization into a chemically intuitive scaffold/functional-group format. While SARMs have been used in the retrospective analysis of SAR discontinuity and identifying underexplored regions of chemistry space, there have been only a few attempts to apply SARMs prospectively in the prioritization of "close-in" analogs.

Lost in translation: The search for an in vitro screen for spermatogenic toxicity.

The last two decades have seen an increasing search for in vitro models that can replace the use of animals for safety testing. We adapted the methods from a recent nonquantitative report of spermatogenesis occurring in ex vivo mouse testis explants and tried to develop them into a screening assay. The model consisted of small pieces of neonatal mouse testis (testis "chunks"), explanted and placed on pillars of agarose or chamber inserts, and cultured at the air-liquid interface.

Predictive Modeling of Response to Pregabalin for the Treatment of Neuropathic Pain Using 6-Week Observational Data: A Spectrum of Modern Analytics Applications.

Purpose: This post hoc analysis used 11 predictive models of data from a large observational study in Germany to evaluate potential predictors of achieving at least 50% pain reduction by week 6 after treatment initiation (50% pain response) with pregabalin (150-600 mg/d) in patients with neuropathic pain (NeP).

Methods: The potential predictors evaluated included baseline demographic and clinical characteristics, such as patient-reported pain severity (0 [no pain] to 10 [worst possible pain]) and pain-related sleep disturbance scores (0 [sleep not impaired] to 10 [severely impaired sleep]) that were collected during clinic visits (baseline and weeks 1, 3, and 6). Baseline characteristics were also evaluated combined with pain change at week 1 or weeks 1 and 3 as potential predictors of end-of-treatment 50% pain response.

Inter-Method Performance Study of Tumor Volumetry Assessment on Computed Tomography Test-Retest Data.

Rationale And Objectives: Tumor volume change has potential as a biomarker for diagnosis, therapy planning, and treatment response. Precision was evaluated and compared among semiautomated lung tumor volume measurement algorithms from clinical thoracic computed tomography data sets. The results inform approaches and testing requirements for establishing conformance with the Quantitative Imaging Biomarker Alliance (QIBA) Computed Tomography Volumetry Profile.

Development of a squamous cell carcinoma mouse model for immunotoxicity testing.

An important component of safety assessment of new pharmaceuticals is evaluation of their potential to increase the risk of developing cancer in humans. The traditional 2-year rodent bioassay often is not feasible or scientifically applicable for evaluation of biotherapeutics. Additionally, it has poor predictive value for non-genotoxic immunosuppressive compounds.

STEP levels are unchanged in pre-frontal cortex and associative striatum in post-mortem human brain samples from subjects with schizophrenia, bipolar disorder and major depressive disorder.

Increased protein levels of striatal-enriched tyrosine phosphatase (STEP) have recently been reported in postmortem schizophrenic cortex. The present study sought to replicate this finding in a separate cohort of postmortem samples and to extend observations to striatum, including subjects with bipolar disorder and major depressive disorder in the analysis. No statistically significant changes between disease and control subjects were found in STEP mRNA or protein levels in dorsolateral prefrontal cortex or associative striatum.

Comparison of the Sysmex XT-2000iV and microscopic bone marrow differential counts in Wistar rats treated with cyclophosphamide, erythropoietin, or serial phlebotomy.

Background: In a previous study, it was demonstrated that bone marrow analysis using the Sysmex XT-2000iV hematology analyzer produced differential counts in untreated rats that were comparable to microscopic differential counts.

Objective: The aim of this study was to modulate hematopoiesis in rats in vivo either through pharmacologic treatment or serial phlebotomy, and to determine whether the Sysmex XT-2000iV could accurately analyze bone marrow quantitative changes when compared with results obtained by microscopy.

Methods: Rats were treated once with 0, 5, 20, and 40 mg/kg cyclophosphamide (CP), 0, 50, 100 IU/kg erythropoietin (EPO) on 4 consecutive days, or serial phlebotomy of 1-2 mL of blood for 4 days.

Three-dimensional lung tumor microenvironment modulates therapeutic compound responsiveness in vitro--implication for drug development.

Three-dimensional (3D) cell culture is gaining acceptance in response to the need for cellular models that better mimic physiologic tissues. Spheroids are one such 3D model where clusters of cells will undergo self-assembly to form viable, 3D tumor-like structures. However, to date little is known about how spheroid biology compares to that of the more traditional and widely utilized 2D monolayer cultures.

Validation of Sysmex XT-2000iV generated quantitative bone marrow differential counts in untreated Wistar rats.

Background: Preclinical drug trials frequently require assessment of bone marrow toxicity in animals to evaluate hematopoietic safety. Since the gold standard, cytologic evaluation, is time consuming and requires highly trained individuals, automated methods remain intriguing.

Objective: The Sysmex XT-2000iV hematology analyzer allows user-developed customizable gating.

The inhibin B response in male rats treated with two drug candidates.

Background: Serum Inhibin B was measured in two studies of known testis-toxic drug candidates.

Methods And Results: Study 1 was for a compound for Hepatitis C, and utilized a 10-week dosing period, followed by mating and necropsy of half of each group, and then a 12-week recovery period for the remaining animals. At the postmating necropsy, 6 of 15 high-dose males had testis lesions; Inhibin B was significantly reduced in all animals in that group.

Multinomial modeling and an evaluation of common data-mining algorithms for identifying signals of disproportionate reporting in pharmacovigilance databases.

Motivation: A principal objective of pharmacovigilance is to detect adverse drug reactions that are unknown or novel in terms of their clinical severity or frequency. One method is through inspection of spontaneous reporting system databases, which consist of millions of reports of patients experiencing adverse effects while taking one or more drugs. For such large databases, there is an increasing need for quantitative and automated screening tools to assist drug safety professionals in identifying drug-event combinations (DECs) worthy of further investigation.

Statistical analysis and compound selection of combinatorial libraries for soluble epoxide hydrolase.

Inhibitors of soluble epoxide hydrolase (sEH) have been extensively pursued as antihypertensive therapies as well as potential treatment for other cardiovascular dysfunctions and prevention of renal damage. In this study we report quantitative structure-activity relationship (QSAR) models for 1223 structurally diverse sEH inhibitors produced by combinatorial library design and synthesis. Daylight fingerprints, MOE 2D and DragonX descriptors were generated for QSAR modeling approaches.

Not a walk in the park: the ECVAM whole embryo culture model challenged with pharmaceuticals and attempted improvements with random forest design.

Background: The European Committee for the Validation of Alternative Methods (ECVAM) supported the development of a linear discriminant embryotoxicity prediction model founded on rat whole embryo culture (Piersma et al. (2004). Altern Lab Anim 32:275–307).

The ensemble bridge algorithm: a new modeling tool for drug discovery problems.

Ensemble algorithms have been historically categorized into two separate paradigms, boosting and random forests, which differ significantly in the way each ensemble is constructed. Boosting algorithms represent one extreme, where an iterative greedy optimization strategy, weak learners (e.g.

The development and validation of a computational model to predict rat liver microsomal clearance.

As the cost of discovering and developing new pharmaceutically relevant compounds continues to rise, it is increasingly important to select the right molecules to prosecute very early in drug discovery. The development of high throughput in vitro assays of hepatic metabolic clearance has allowed for vast quantities of data generation; however, these large screens are still costly and remain dependant on animal usage. To further expand the value of these screens and ultimately aid in animal usage reduction, we have developed an in silico model of rat liver microsomal (RLM) clearance.

Beyond pass/fail: a procedure for evaluating the effect of carryover in bioanalytical LC/MS/MS methods.

Eliminating carryover from bioanalytical methods can be a time and resource consuming process. While it is necessary to investigate root causes of the carryover and reduce problem areas, complete elimination of carryover may not be practical or even possible. The purpose of this paper is to suggest an avenue to investigate the effect of carryover within an analytical run rather than employ a simple pass/fail criterion.

Identifying promising compounds in drug discovery: genetic algorithms and some new statistical techniques.

Throughout the drug discovery process, discovery teams are compelled to use statistics for making decisions using data from a variety of inputs. For instance, teams are asked to prioritize compounds for subsequent stages of the drug discovery process, given results from multiple screens. To assist in the prioritization process, we propose a desirability function to account for a priori scientific knowledge; compounds can then be prioritized based on their desirability scores.

Porcine brain microvessel endothelial cells as an in vitro model to predict in vivo blood-brain barrier permeability.

The objective of the study was to establish primary cultured porcine brain microvessel endothelial cells (PBMECs) as an in vitro model to predict the blood-brain barrier (BBB) permeability in vivo. The intercellular tight junction formation of PBMECs was examined by electron microscopy and measured by transendothelial electrical resistance (TEER). The mRNA expression of several BBB transporters in PBMECs was determined by reverse transcriptionpolymerase chain reaction analysis.

An efficient approach for the rapid assessment of oral rat exposures for new chemical entities in drug discovery.

Present study aims to improve efficiency and capacity of in vivo rat pharmacokinetic studies for rapid assessment of systemic exposure (AUC and C(max)) of new chemical entities. Plasma concentration-time profiles in rats from structurally diverse compounds were extracted from the Pfizer database. AUC(0-8) was calculated with 7 data points or a reduced subset of 3 data points.