Vladimir Svetnik

• PhD
• Head of Department at Merck & Co.

PURPOSE Eastern Cooperative Oncology Group performance status (ECOG PS) is a key confounder in comparative effectiveness research, predicting treatment and survival, but is often incomplete in electronic health records (EHRs). Imputation on the basis of classification metrics alone may introduce differences in survival between patients with known a...

In drug discovery, the reliability of compound screening based on manual assessments is compromised by potential bias, while existing methods lack robust risk control measures. To address these challenges, we introduced conformal selection as an enhanced approach to optimize the compound screening process with balanced risks and benefits. Leveragin...

Background Current methods of measuring disease progression of neurodegenerative disorders, including Parkinson's disease (PD), largely rely on composite clinical rating scales, which are prone to subjective biases and lack the sensitivity to detect progression signals in a timely manner. Digital health technology (DHT)-derived measures offer poten...

We present a conformal inference method for constructing lower prediction bounds for survival times from right-censored data, extending recent approaches designed for type-I censoring. This method imputes unobserved censoring times using a suitable model, and then analyzes the imputed data using weighted conformal inference. This approach is theore...

In drug discovery, the reliability of compound screening based on manual assessments is compromised by potential bias, while existing methods lack robust risk control measures. To address these challenges, we introduced conformal selection as an enhanced approach to optimize the compound screening process with balanced risks and benefits. Leveragin...

Background: Current methods of measuring disease progression of neurodegenerative disorders, including Parkinson's disease (PD), largely rely on composite clinical rating scales, which are prone to subjective biases and lack the sensitivity to detect progression signals in a timely manner. Digital health technology (DHT)-derived measures offer pote...

The quantitative structure–activity relationship (QSAR) regression model is a commonly used technique for predicting the biological activities of compounds using their molecular descriptors. Besides accurate activity estimation, obtaining a prediction uncertainty metric like a prediction interval is highly desirable. Quantifying prediction uncertai...

With the growing commonality of multi‐omics datasets, there is now increasing evidence that integrated omics profiles lead to more efficient discovery of clinically actionable biomarkers that enable better disease outcome prediction and patient stratification. Several methods exist to perform host phenotype prediction from cross‐sectional, single‐o...

Dear Editor, Dysfunction of the circadian timing system is a distinguishing feature of many neurodegenerative diseases [1]. We report here on an apparent phase advance in the self-selected bedtimes of patients with Alzheimer’s disease (AD) observed during baseline of a clinical trial. This analysis used baseline data from two randomized controlled...

The quantitative structure-activity relationship (QSAR) regression model is a commonly used technique for predicting biological activities of compounds using their molecular descriptors. Predictions from QSAR models can help, for example, to optimize molecular structure; prioritize compounds for further experimental testing; and estimate their toxi...

Background We used baseline polysomnography (PSG) data obtained during the clinical program development for suvorexant to compare the PSG profiles of people with Alzheimer's disease and insomnia (ADI) versus age-matched elderly individuals with insomnia (EI). Methods Sleep laboratory Baseline PSG data from participants age 55–80 years from 2 trial...

With the growing commonality of multi-omics datasets, there is now increasing evidence that integrated omics profiles lead to the more efficient discovery of clinically actionable biomarkers that enable better disease outcome prediction and patient stratification. Several methods exist to perform host phenotype prediction from cross-sectional, sing...

Chronic diseases often require continuing care, and early response to treatment can be an important predictor of long‐term efficacy. Often, an apparent lack of early efficacy may lead to discontinuation of treatment, with the decision made either by clinicians or by the patients themselves. Thus, it is important to determine whether or not a desire...

The orexin receptor antagonist suvorexant was previously reported to significantly improve total sleep time (TST), by 28 min per night versus placebo after 4 weeks, in a sleep laboratory polysomnography (PSG) study of patients with Alzheimer's disease and insomnia. The study included an exploratory evaluation of a consumer‐grade wearable “watch” de...

A reciprocal LASSO (rLASSO) regularization employs a decreasing penalty function as opposed to conventional penalization approaches that use increasing penalties on the coefficients, leading to stronger parsimony and superior model selection relative to traditional shrinkage methods. Here we consider a fully Bayesian formulation of the rLASSO probl...

We evaluated a single‐item Patient Global Impression‐Severity (PGI‐S) scale for assessing insomnia severity during the clinical development programme for suvorexant. The analyses used data from two randomised, double‐blind, placebo‐controlled, 3‐month, Phase III clinical trials of suvorexant in patients with Diagnostic and Statistical Manual of Men...

Introduction Suvorexant, an orexin receptor antagonist, improved total sleep time (TST) in a sleep laboratory polysomnography (PSG) study of patients with Alzheimer’s disease (AD) and insomnia. The study included a pilot evaluation of an actigraphy watch for continuously recording patient’s sleep and daytime activity. We report on the utility of th...

Introduction Experimental investigation of sleep-wake dynamics in animals is an important part of pharmaceutical development. It typically involves recording of electroencephalogram, electromyogram, locomotor activity, and electrooculogram. Visual identification, or scoring, of the sleep-wake states from these recordings is time-consuming. We sough...

Introduction Suvorexant, an orexin receptor antagonist that enables sleep to occur via competitive antagonism of wake-promoting orexins, improved total sleep time (TST) in a sleep laboratory polysomnography (PSG) study of patients with AD and insomnia. Here we report on the effects of suvorexant on sleep architecture in the study. Methods This was...

Protein redesign and engineering has become an important task in pharmaceutical research and development. Recent advances in technology have enabled efficient protein redesign by mimicking natural evolutionary mutation, selection and amplification steps in the laboratory environment. For any given protein, the number of possible mutations is astron...

Background Experimental investigation of sleep-wake dynamics in animals is an important part of pharmaceutical development. Typically, it involves recording of electroencephalogram, electromyogram, locomotor activity, and electrooculogram. Visual identification, or scoring, of the sleep-wake states from these recordings is time-consuming. We sought...

A reciprocal LASSO (rLASSO) regularization employs a decreasing penalty function as opposed to conventional penalization methods that use increasing penalties on the coefficients, leading to stronger parsimony and superior model selection relative to traditional shrinkage methods. Here we consider a fully Bayesian formulation of the rLASSO problem,...

Objective: The determinants of sleep quality (sQUAL) are poorly understood. We evaluated how well a large number of objective polysomnography (PSG) parameters can predict sQUAL in insomnia patients participating in trials of sleep medications or placebo. Methods: PSG recordings over multiple nights from two clinical drug development programs inv...

Quantitative structure-activity relationship (QSAR) is a very commonly used technique for predicting biological activity of a molecule using information contained in the molecular descriptors. The large number of compounds and descriptors and sparseness of descriptors pose important challenges to traditional statistical methods and machine learning...

The need for assessment of agreement of biomarkers is ubiquitous in drug development. In this study, we focus on scaled agreement indices including within-subject coefficient of variation, intraclass correlation coefficient, and concordance correlation coefficient. We illustrate, by both simulated and real life datasets, the usage and added value o...

The concordance correlation coefficient (CCC) is a widely used scaled index in the study of agreement. In this article, we propose estimating the CCC by a unified Bayesian framework that can (1) accommodate symmetric or asymmetric and light- or heavy-tailed data; (2) select model from several candidates; and (3) address other issues frequently enco...

Objectives: To examine the duration and frequency of wake bouts underlying the wakefulness-after-sleep-onset (WASO) reduction with suvorexant. Methods: We analyzed polysomnogram recordings from clinical trials involving 1518 insomnia patients receiving suvorexant (40/30mg, 20/15mg) or placebo to determine: 1) the number of, and time spent in, lo...

Deep neural networks (DNNs) are complex computational models that have found great success in many artificial intelligence applications, such as computer vision and natural language processing. In the past four years, DNNs also generated promising results for quantitative structure-activity relationship (QSAR) tasks. Previous work showed that DNNs...

Introduction Orexin receptor (OX1R, OX2R) antagonism induces sleep architecture characterized by increases in both NREM and REM reminiscent of unmedicated sleep. REM sleep is thought to be controlled in part by noradrenergic neurons of the locus coeruleus (LC), a site of selective OX1R expression. This work utilizes selective DORA and 2-SORA antago...

Introduction Different from our previously reported studies examining the bivariate correlation between each of the sleep parameters assessed objectively by polysomnography (PSG) and patient-reported sleep quality (SQ), we investigated how accurately a large number of PSG parameters can jointly predict (explain) SQ. Methods PSG recordings from two...

Previous studies of the differences between patients with insomnia and good sleepers with regard to quantitative electroencephalographic measures have mostly utilized small samples and consequently had limited ability to account for potentially important confounding factors of age, sex and part of the night. We conducted a power spectral analysis u...

The objective of this study was to evaluate sleep electrophysiology in healthy subjects after bedtime administration of therapeutic doses of two insomnia treatments - the orexin receptor antagonist suvorexant or the GABAergic agonist zolpidem. Eighteen healthy men received single bedtime doses of suvorexant 20mg, zolpidem 10mg, or placebo in a doub...

Orexin neuropeptides regulate sleep/wake through orexin receptors (OX1R, OX2R); OX2R is the predominant mediator of arousal promotion. The potential for single OX2R antagonism to effectively promote sleep has yet to be demonstrated in humans. MK-1064 is an OX2R-single antagonist. Preclinically, MK-1064 promotes sleep and increases both rapid eye mo...

Background: The orexin receptor antagonist, suvorexant, is approved for treating insomnia at a maximum dose of 20 mg. We evaluated its effects on sleep architecture. Methods: The analyses included pooled polysomnography data from two similar randomized, double-blind, placebo-controlled, 3-month trials evaluating two age-adjusted (non-elderly/eld...

Neural networks were widely used for Quantitative Structure-Activity Relationships (QSAR), in the 1990's. Because of various practical issues (e.g. slow on large problems, difficult to train, prone to over-fitting, etc.), they were superseded by more robust methods like Support Vector Machine (SVM) and Random Forest (RF), which arose in the early 2...

This chapter describes a very important application of statistical methods to drug discovery, namely quantitative structure-activity relationship (QSAR) models. These models are most often used in the lead optimization stage, when a few families of molecules have been identified as active in vitro against the biological target of interest. The chap...

Study objectives: Suvorexant, an orexin receptor antagonist, improves sleep in healthy subjects (HS) and patients with insomnia. We compared the electroencephalographic (EEG) power spectral density (PSD) profile of suvorexant with placebo using data from a phase 2 trial in patients with insomnia. We also compared suvorexant's PSD profile with the...

Non-nucleoside reverse transcriptase inhibitors are important antiretroviral agents for the treatment of human immunodeficiency virus. Some non-nucleoside reverse transcriptase inhibitors, in particular efavirenz, have prominent effects on sleep, cognition and psychiatric variables that limit their tolerability. To avoid confounds due to drug–drug...

Introduction Spectral analysis has been used to quantify differences in the sleep EEG between primary insomniacs (PI) and good sleeper controls (GSC). Previous studies have been based on relatively small samples with varying inclusion criteria, and have not typically examined the effects of important factors such as age, gender, and sleep period of...

The International Pharmaco-EEG Society (IPEG) presents guidelines summarising the requirements for the recording and computerised evaluation of pharmaco-sleep data in man. Over the past years, technical and data-processing methods have advanced steadily, thus enhancing data quality and expanding the palette of sleep assessment tools that can be use...

To study the characteristics of unintentional muscle activities in clinical EEG, and to develop a high-throughput method to reduce them for better revealing drug or biological effects on EEG. Two clinical EEG datasets are involved. Pure muscle signals are extracted from EEG using Independent Component Analysis (ICA) for studying their characteristi...

To explore the effect of gaboxadol on NREM EEG in transient insomnia using power spectral analysis and evaluate the response between men and women. This was a randomized, double-blind, 3-way, parallel-group transient insomnia study in 22 sleep laboratories. After a baseline night (N1), subjects underwent a 4-h phase-advance of their habitual sleep...

After a review of the ocular artifact reduction literature, a high-throughput method designed to reduce the ocular artifacts in multichannel continuous EEG recordings acquired at clinical EEG laboratories worldwide is proposed. The proposed method belongs to the category of component-based methods, and does not rely on any electrooculography (EOG)...

to evaluate cyclic alternating pattern (CAP) in a phase advance model of transient insomnia and the effects of gaboxadol and zolpidem. a randomized, double-blind, cross-over study in which habitual sleep time was advanced by 4 h. 6 sleep research laboratories in US PARTICIPANTS: 55 healthy subjects (18-57 y) Gaboxadol 15 mg (GBX), zolpidem 10 mg (Z...

With the increasing popularity of using electroencephalography (EEG) to reveal the treatment effect in drug development clinical trials, the vast volume and complex nature of EEG data compose an intriguing, but challenging, topic. In this paper the statistical analysis methods recommended by the EEG community, along with methods frequently used in...

INTRODUCTION C NMR spectroscopy plays a significant role in the identification and classification of unknown organic compounds from natural products. This is largely due to the wellknown and exquisite dependence of the C chemical shift and proton splitting pattern of each carbon atom on its local chemical environment and its number of attached prot...

This paper proposes a new automatic hypothesis-generation algorithm for structure–activity relationship (SAR) rules, which is capable of investigating chemical compound activities in the context of multiple substructure interactions. The algorithm is formulated as an optimization problem based on a carefully selected criterion, APostDiff(s), and th...

High-density oligonucleotide arrays allow researchers to measure mRNA transcript abundance for thou- sands of genes on a single array. The large number of genes, multiple sources of variation, and typically small number of experimental units (EUs) combine to make analysis of data from these arrays challenging. We describe our experience in applying...

To evaluate the performance of 2 automated systems, Morpheus and Somnolyzer24X7, with various levels of human review/editing, in scoring polysomnographic (PSG) recordings from a clinical trial using zolpidem in a model of transient insomnia. 164 all-night PSG recordings from 82 subjects collected during 2 nights of sleep, one under placebo and one...

A classification and regression tool, J. H. Friedman's Stochastic Gradient Boosting (SGB), is applied to predicting a compound's quantitative or categorical biological activity based on a quantitative description of the compound's molecular structure. Stochastic Gradient Boosting is a procedure for building a sequence of models, for instance regres...

A complete list of 60 tissues and cell lines hybridized to the predicted transcript arrays

A list of six tissues and cell lines hybridized to the chromosome 20 genomic tiling arrays

A comparison of EVG predictions with RefSeq sequencesP

A complete list of 48,614 transcripts in the PTI that were represented on the set of predicted transcript arrays

The eight tissues and cell lines hybridized to the chromosome 22 genomic tiling arrays

Leo Breiman’s Random Forest ensemble learning procedure is applied to the problem of Quantitative Structure-Activity Relationship (QSAR) modeling for pharmaceutical molecules. This entails using a quantitative description of a compound’s molecular structure to predict that compound’s biological activity as measured in an in vitro assay. Without any...

Computational and microarray-based experimental approaches were used to generate a comprehensive transcript index for the human genome. Oligonucleotide probes designed from approximately 50,000 known and predicted transcript sequences from the human genome were used to survey transcription from a diverse set of 60 tissues and cell lines using ink-j...

A wrapper variable selection procedure is proposed for use with learning machines that generate a measure of variable importance, such as Random Forest. The procedure is based on iteratively removing low-ranking variables and assessing the learning machine performance by cross-validation. The procedure is implemented for Random Forest on some QSAR...

A new classification and regression tool, Random Forest, is introduced and investigated for predicting a compound's quantitative or categorical biological activity based on a quantitative description of the compound's molecular structure. Random Forest is an ensemble of unpruned classification or regression trees created by using bootstrap samples...

A simple database of (13)C/(1)H-(13)C spectral lists for 11 673 natural products was created in standard commercial database format. Over 50% of the spectra were predicted using HOSE code descriptors derived from the 50% of spectra having experimental values. Prediction errors obtained by prediction of and comparison to the experimental spectra rev...

Outlying samples are sought in a very high-dimensional data set, a library of mass spectra. Such samples are considered novel from the chemical structure point of view and are identified for further investigation of their potential biological activity. The support vector machine algorithm for domain description (Tax & Duin 1999; Schölkopf et al. 20...