Emergence of the silicon human and network targeting drugs

in European Journal of Pharmaceutical Sciences (2012), 46(4), 190-197

The development of disease may be characterized as a pathological shift of homeostasis; the main goal of contemporary drug treatment is, therefore, to return the pathological homeostasis back to the ... [more ▼]

The development of disease may be characterized as a pathological shift of homeostasis; the main goal of contemporary drug treatment is, therefore, to return the pathological homeostasis back to the normal physiological range. From the view point of systems biology, homeostasis emerges from the interactions within the network of biomolecules (e.g. DNA, mRNA, proteins), and, hence, understanding how drugs impact upon the entire network should improve their efficacy at returning the network (body) to physiological homeostasis. Large, mechanism-based computer models, such as the anticipated human whole body models (silicon or virtual human), may help in the development of such network-targeting drugs. Using the philosophical concept of weak and strong emergence, we shall here take a more general look at the paradigm of network-targeting drugs, and propose our approaches to scale the strength of strong emergence. We apply these approaches to several biological examples and demonstrate their utility to reveal principles of bio-modeling. We discuss this in the perspective of building the silicon human. [less ▲]

Revolutionizing medicine in the 21(st) century through systems approaches

in Biotechnology Journal (2012), 7(8), 937-1054

Personalized medicine is a term for a revolution in medicine that envisions the individual patient as the central focus of healthcare in the future. The term "personalized medicine", however, fails to ... [more ▼]

Personalized medicine is a term for a revolution in medicine that envisions the individual patient as the central focus of healthcare in the future. The term "personalized medicine", however, fails to reflect the enormous dimensionality of this new medicine that will be predictive, preventive, personalized, and participatory-a vision of medicine we have termed P4 medicine. This reflects a paradigm change in how medicine will be practiced that is revolutionary rather than evolutionary. P4 medicine arises from the confluence of a systems approach to medicine and from the digitalization of medicine that creates the large data sets necessary to deal with the complexities of disease. We predict that systems approaches will empower the transition from conventional reactive medical practice to a more proactive P4 medicine focused on wellness, and will reverse the escalating costs of drug development an will have enormous social and economic benefits. Our vision for P4 medicine in 10 years is that each patient will be associated with a virtual data cloud of billions of data points and that we will have the information technology for healthcare to reduce this enormous data dimensionality to simple hypotheses about health and/or disease for each individual. These data will be multi-scale across all levels of biological organization and extremely heterogeneous in type - this enormous amount of data represents a striking signal-to-noise (S/N) challenge. The key to dealing with this S/N challenge is to take a "holistic systems approach" to disease as we will discuss in this article. [less ▲]

Candidate mutations for early-onset lung cancer by family genome sequencing

Poster (2011, July)

Early-onset lung cancer has been studied as a rare, but distinct, sub-type of lung cancer. Genome-wide association studies (GWAS) have linked several genes with this form of malignancy. We sequenced the ... [more ▼]

Early-onset lung cancer has been studied as a rare, but distinct, sub-type of lung cancer. Genome-wide association studies (GWAS) have linked several genes with this form of malignancy. We sequenced the genomes of a family quartet in which one of the offspring was diagnosed with early-onset lung cancer at about 48 years of age. The family has a history of heavy smoking and the father had in the past been diagnosed with head and neck cancer. The DNA source was blood, which leads us to concentrate our analysis on Mendelian inheritance models. To make the inheritance pattern explicit, we establish the parental origin of the offspring’s genomes through phasing of their chromosomes. This helps identify whether mutations in the proband came from the father or the mother. More than 18 million sequence variants were initially identified in the proband through comparison to the hg19 reference genome. We reduce this list to fewer than 200 potentially functional variants (e.g. single nucleotide variations and short indels) present in the genomes of the proband and at least one parent, by applying a series of filters. We refine the list of candidate mutations further by comparison to gene candidates from GWAS studies and genes that are mutated in lung cancer tissue as recorded by The Cancer Genome Atlas. The results of our analysis are discussed and conclusions about possible causative mutations for early-onset lung cancer are drawn. [less ▲]

Parkinson’s disease mouse models in translational research

in Mammalian Genome (2011), 22(7-8), 401-19

Animal models with high predictive power are a prerequisite for translational research. The closer the similarity of a model to Parkinson's disease (PD), the higher is the predictive value for clinical ... [more ▼]

Animal models with high predictive power are a prerequisite for translational research. The closer the similarity of a model to Parkinson's disease (PD), the higher is the predictive value for clinical trials. An ideal PD model should present behavioral signs and pathology that resemble the human disease. The increasing understanding of PD stratification and etiology, however, complicates the choice of adequate animal models for preclinical studies. An ultimate mouse model, relevant to address all PD-related questions, is yet to be developed. However, many of the existing models are useful in answering specific questions. An appropriate model should be chosen after considering both the context of the research and the model properties. This review addresses the validity, strengths, and limitations of current PD mouse models for translational research. [less ▲]

Systems medicine and integrated care to combat chronic noncommunicable diseases

in Genome Medicine (2011), 3(7), 43-47

We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic ... [more ▼]

We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems. [less ▲]

Finding and sharing: new approaches to registries of databases and services for the biomedical sciences

in Database: the Journal of Biological Databases and Curation (2010), Jul 6

The recent explosion of biological data and the concomitant proliferation of distributed databases make it challenging for biologists and bioinformaticians to discover the best data resources for their ... [more ▼]

The recent explosion of biological data and the concomitant proliferation of distributed databases make it challenging for biologists and bioinformaticians to discover the best data resources for their needs, and the most efficient way to access and use them. Despite a rapid acceleration in uptake of syntactic and semantic standards for interoperability, it is still difficult for users to find which databases support the standards and interfaces that they need. To solve these problems, several groups are developing registries of databases that capture key metadata describing the biological scope, utility, accessibility, ease-of-use and existence of web services allowing interoperability between resources. Here, we describe some of these initiatives including a novel formalism, the Database Description Framework, for describing database operations and functionality and encouraging good database practise. We expect such approaches will result in improved discovery, uptake and utilization of data resources. Database URL: http://www.casimir.org.uk/casimir_ddf. [less ▲]

Diseases as network perturbations

in Current Opinion in Biotechnology (2010), 21(4), 566-571

The tremendous amount of the data obtained from the study of complex biological systems changes our view on the pathogenesis of human diseases. Instead of looking at individual components of biological ... [more ▼]

The tremendous amount of the data obtained from the study of complex biological systems changes our view on the pathogenesis of human diseases. Instead of looking at individual components of biological processes, we focus our attention more on the interaction and dynamics of biological systems. A network representation and analysis of the physiology and pathophysiology of biological systems is an effective way to study their complex behavior. Specific perturbations can trigger cascades of failures, which lead to the malfunctioning of cellular networks and as a result to the development of specific diseases. In this review we discuss recent developments in the field of disease network analysis and highlight some of the topics and views that we think are important for understanding network-based disease mechanisms. [less ▲]

The bumpy road to personalized healthcare.

in European Biotechnology Science and Industry News (2010), 9(7-8),

EuroPhenome: a repository for high-throughput mouse phenotyping data

in Nucleic Acids Research (2010), 38(1), 577-585

The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and ... [more ▼]

The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated highthroughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress .har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies. [less ▲]

Reverse engineering and verification of gene networks: principles, assumptions, and limitations of present methods and future perspectives.

in Journal of Biotechnology (2009), 144(3), 190-203

Reverse engineering of gene networks aims at revealing the structure of the gene regulation network in a biological system by reasoning backward directly from experimental data. Many methods have recently ... [more ▼]

Reverse engineering of gene networks aims at revealing the structure of the gene regulation network in a biological system by reasoning backward directly from experimental data. Many methods have recently been proposed for reverse engineering of gene networks by using gene transcript expression data measured by microarray. Whereas the potentials of the methods have been well demonstrated, the assumptions and limitations behind them are often not clearly stated or not well understood. In this review, we first briefly explain the principles of the major methods, identify the assumptions behind them and pinpoint the limitations and possible pitfalls in applying them to real biological questions. With regard to applications, we then discuss challenges in the experimental verification of gene networks generated from reverse engineering methods. We further propose an optimal experimental design for allocating sampling schedule and possible strategies for reducing the limitations of some of the current reverse engineering methods. Finally, we examine the perspectives for the development of reverse engineering and urge the need to move from revealing network structure to the dynamics of biological systems. [less ▲]