Models and methods for power monolithic microwave integrated circuits

Computer aided design of Monolithic Microwave Integrated Circuits (MMICs) depends critically on active device models that are accurate, computationally efficient, and easily extracted from measurements or device simulators. Empirical models of active electron devices, which are based on actual device measurements, do not provide a detailed description of the electron device physics. However they are numerically efficient and quite accurate. These characteristics make them very suitable for MMIC design in the framework of commercially available CAD tools. In the empirical model formulation it is very important to separate linear memory effects (parasitic effects) from the nonlinear effects (intrinsic effects). Thus an empirical active device model is generally described by an extrinsic linear part which accounts for the parasitic passive structures connecting the nonlinear intrinsic electron device to the external world. An important task circuit designers deal with is evaluating the ultimate potential of a device for specific applications. In fact once the technology has been selected, the designer would choose the best device for the particular application and the best device for the different blocks composing the overall MMIC. Thus in order to accurately reproducing the behaviour of different-in-size devices, good scalability properties of the model are necessarily required. Another important aspect of empirical modelling of electron devices is the mathematical (or equivalent circuit) description of the nonlinearities inherently associated with the intrinsic device. Once the model has been defined, the proper measurements for the characterization of the device are performed in order to identify the model. Hence, the correct measurement of the device nonlinear characteristics (in the device characterization phase) and their reconstruction (in the identification or even simulation phase) are two of the more important aspects of empirical modelling. This thesis presents an original contribution to nonlinear electron device empirical modelling treating the issues of model scalability and reconstruction of the device nonlinear characteristics. The scalability of an empirical model strictly depends on the scalability of the linear extrinsic parasitic network, which should possibly maintain the link between technological process parameters and the corresponding device electrical response. Since lumped parasitic networks, together with simple linear scaling rules, cannot provide accurate scalable models, either complicate technology-dependent scaling rules or computationally inefficient distributed models are available in literature. This thesis shows how the above mentioned problems can be avoided through the use of commercially available electromagnetic (EM) simulators. They enable the actual device geometry and material stratification, as well as losses in the dielectrics and electrodes, to be taken into account for any given device structure and size, providing an accurate description of the parasitic effects which occur in the device passive structure. It is shown how the electron device behaviour can be described as an equivalent two-port intrinsic nonlinear block connected to a linear distributed four-port passive parasitic network, which is identified by means of the EM simulation of the device layout, allowing for better frequency extrapolation and scalability properties than conventional empirical models. Concerning the issue of the reconstruction of the nonlinear electron device characteristics, a data approximation algorithm has been developed for the exploitation in the framework of empirical table look-up nonlinear models. Such an approach is based on the strong analogy between timedomain signal reconstruction from a set of samples and the continuous approximation of device nonlinear characteristics on the basis of a finite grid of measurements. According to this criterion, nonlinear empirical device modelling can be carried out by using, in the sampled voltage domain, typical methods of the time-domain sampling theory.

Role of SP-A gene polymorphism in lung transplantation

Lung transplantation is a widely accepted therapeutic option for end stage lung disease. Clinical outcome is yet challenged by primary graft failure responsible for the majority of the early mortality, by chronic allograft dysfunction and chronic rejection accounting for more than 30% of deaths after the third postoperative year. Pulmonary surfactant proteins (SP) A, B, C and D are one of the first host defense mechanisms the lung can mount. SP-A in particular, produced by the type II pneumocytes, is active in the innate and adaptive immune system being an opsonin, but also regulating the macrophage and lymphocyte response. The main hypothesis for this project is that pulmonary surfactant protein A polymorphism may determine the early and long term lung allograft survival. Of note SP-A biologic activity seems to be genetically determined and SP-A polymorphisms have been associated to various lung disease. The two SP-A genes SP-A1 and SP-A2 have several polymorphisms within the coding region, SP-A1 (6A, 6A2-20), and SP-A2(1A, 1A0-13). The SP-A gene expression is regulated by cAMP, TTF-1 and glucocorticoids. In vitro studies have indicated that SP-A1 and SP-A2 gene variants may have a variable response to glucocorticoids. We proposed to determine if SP-A gene polymorphism predicts primary graft dysfunction and/or chronic lung allograft dysfunction and if SP-A may serve as a biomarker of lung allograft dysfunction. We also proposed to study the interaction between immunosuppressive drugs and SP-A expression and determine whether this is dependent on SP-A polymorphisms. This study will generate novel information improving our understanding of lung allograft dysfunction. It is conceivable that the information will stimulate the interest for a multi centre study to investigate if SP-A polymorphism may be integrated in the donor lung selection criteria and/or to implement post transplant tailored immunosuppression.

Ricerca e applicazione di metodologie ecotossicologiche nel monitoraggio di ambienti marino-costieri: Sviluppo di nuovi bioassay e biomarker

Obiettivo del lavoro è stato lo sviluppo e la validazione di nuovi bioassay e biomarker quali strumenti da utilizzare in un approccio ecotossicologico integrato per il biomonitoraggio di ambienti marino-costieri interessati da impatto antropico negli organismi che vivono in tali ambienti. L’ambiente reale impiegato per l’applicazione in campo è la Rada di Augusta (Siracusa, Italia). Una batteria di bioassay in vivo e in vitro è stata indagata quale strumento di screening per la misura della tossicità dei sedimenti. La batteria selezionata ha dimostrato di possedere i requisiti necessari ad un applicazione di routine nel monitoraggio di ambienti marino costieri. L’approccio multimarker basato sull’impiego dell’organismo bioindicatore Mytilus galloprovincialis in esperimenti di traslocazione ha consentito di valutare il potenziale applicativo di nuovi biomarker citologici e molecolari di stress chimico parallelamente a biomarker standardizzati di danno genotossico ed esposizione a metalli pesanti. I mitili sono stati traslocati per 45 giorni nei siti di Brucoli (SR) e Rada di Augusta, rispettivamente sito di controllo e sito impattato. I risultati ottenuti supportano l’applicabilità delle alterazioni morfometriche dei granulociti quale biomarker di effetto, direttamente correlato allo stato di salute degli organismi che vivono in un dato ambiente. Il significativo incremento dell’area dei lisosomi osservato contestualmente potrebbe riflettere un incremento dei processi degradativi e dei processi autofagici. I dati sulla sensibilità in campo suggeriscono una valida applicazione della misura dell’attività di anidrasi carbonica in ghiandola digestiva come biomarker di stress in ambiente marino costiero. L’utilizzo delle due metodologie d’indagine (bioassay e biomarker) in un approccio ecotossicologico integrato al biomonitoraggio di ambienti marino-costieri offre uno strumento sensibile e specifico per la valutazione dell’esposizione ad inquinanti e del danno potenziale esercitato dagli inquinanti sugli organismi che vivono in un dato ambiente, permettendo interventi a breve termine e la messa a punto di adeguati programmi di gestione sostenibile dell’ambiente.

Predicting and monitoring cancer treatment response with diffusion-weighted MRI

An imaging biomarker that would provide for an early quantitative metric of clinical treatment response in cancer patients would provide for a paradigm shift in cancer care. Currently, nonimage based clinical outcome metrics include morphology, clinical, and laboratory parameters, however, these are obtained relatively late following treatment. Diffusion-weighted MRI (DW-MRI) holds promise for use as a cancer treatment response biomarker as it is sensitive to macromolecular and microstructural changes which can occur at the cellular level earlier than anatomical changes during therapy. Studies have shown that successful treatment of many tumor types can be detected using DW-MRI as an early increase in the apparent diffusion coefficient (ADC) values. Additionally, low pretreatment ADC values of various tumors are often predictive of better outcome. These capabilities, once validated, could provide for an important opportunity to individualize therapy thereby minimizing unnecessary systemic toxicity associated with ineffective therapies with the additional advantage of improving overall patient health care and associated costs. In this report, we provide a brief technical overview of DW-MRI acquisition protocols, quantitative image analysis approaches and review studies which have implemented DW-MRI for the purpose of early prediction of cancer treatment response.

Reverse-translational biomarker validation of Abnormal Repetitive Behaviors in mice: an illustration of the 4P's modeling approach

The NIMH's new strategic plan, with its emphasis on the "4P's" (Prediction, Pre-emption, Personalization, and Populations) and biomarker-based medicine requires a radical shift in animal modeling methodology. In particular 4P's models will be non-determinant (i.e. disease severity will depend on secondary environmental and genetic factors); and validated by reverse-translation of animal homologues to human biomarkers. A powerful consequence of the biomarker approach is that different closely related disorders have a unique fingerprint of biomarkers. Animals can be validated as a highly specific model of a single disorder by matching this 'fingerprint'; or as a model of a symptom seen in multiple disorders by matching common biomarkers. Here we illustrate this approach with two Abnormal Repetitive Behaviors (ARBs) in mice: stereotypies and barbering (hair pulling). We developed animal versions of the neuropsychological biomarkers that distinguish human ARBs, and tested the fingerprint of the different mouse ARBs. As predicted, the two mouse ARBs were associated with different biomarkers. Both barbering and stereotypy could be discounted as models of OCD (even though they are widely used as such), due to the absence of limbic biomarkers which are characteristic of OCD and hence are necessary for a valid model. Conversely barbering matched the fingerprint of trichotillomania (i.e. selective deficits in set-shifting), suggesting it may be a highly specific model of this disorder. In contrast stereotypies were correlated only with a biomarker (deficits in response shifting) correlated with stereotypies in multiple disorders, suggesting that animal stereotypies model stereotypies in multiple disorders.

Design, conduct, and analysis of a multicenter, pharmacogenomic, biomarker study in matched patients with severe sepsis treated with or without drotrecogin Alfa (activated)

A genomic biomarker identifying patients likely to benefit from drotrecogin alfa (activated) (DAA) may be clinically useful as a companion diagnostic. This trial was designed to validate biomarkers (improved response polymorphisms (IRPs)). Each IRP (A and B) contains two single nucleotide polymorphisms that were associated with a differential DAA treatment effect.

Anticipatory cognitive stress appraisal and the acute procoagulant stress response in men

OBJECTIVE: Acute mental stress elicits blood hypercoagulability. Following a transactional stress model, we investigated whether individuals who anticipate stress as more threatening, challenging, and as exceeding their coping skills show greater stress reactivity of the coagulation activation marker D-dimer, indicating fibrin generation in plasma. METHODS: Forty-seven men (mean age 44 +/- 14 years; mean blood pressure [MBP] 101 +/- 12 mm Hg; mean body mass index [BMI] 26 +/- 3 kg/m(2)) completed the Primary Appraisal Secondary Appraisal (PASA) scale before undergoing the Trier Social Stress Test (combination of mock job interview and mental arithmetic task). Heart rate, blood pressure, plasma catecholamines, and D-dimer levels were measured before and after stress, and during recovery up to 60 minutes poststress. RESULTS: Hemodynamic measures, catecholamines, and D-dimer changed across all time points (p values <.001). The PASA "Stress Index" (integrated measure of transactional stress perception) correlated with total D-dimer area under the curve (AUC) between rest and 60 minutes poststress (r = 0.30, p = .050) and with D-dimer change from rest to immediately poststress (r = 0.29, p = .046). Primary appraisal (combined "threat" and "challenge") correlated with total D-dimer AUC (r = 0.37, p = .017), D-dimer stress change (r = 0.41, p = .004), and D-dimer recovery (r = 0.32, p = .042). "Challenge" correlated more strongly with D-dimer stress change than "threat" (p = .020). Primary appraisal (DeltaR(2) = 0.098, beta = 0.37, p = .019), and particularly its subscale "challenge" (DeltaR(2) = 0.138, beta = 0.40, p = .005), predicted D-dimer stress change independently of age, BP, BMI, and catecholamine change. CONCLUSIONS: Anticipatory cognitive appraisal determined the extent of coagulation activation to and recovery from stress in men. Particularly individuals who anticipated the stressor as more challenging and also more threatening had a greater fibrin stress response.

Effect of oral melatonin on the procoagulant response to acute psychosocial stress in healthy men: a randomized placebo-controlled study

Acute mental stress is a potent trigger of acute coronary syndromes. Catecholamine-induced hypercoagulability with acute stress contributes to thrombus growth after coronary plaque rupture. Melatonin may diminish catecholamine activity. We hypothesized that melatonin mitigates the acute procoagulant stress response and that this effect is accompanied by a decrease in the stress-induced catecholamine surge. Forty-five healthy young men received a single oral dose of either 3 mg melatonin (n = 24) or placebo medication (n = 21). One hour thereafter, they underwent a standardized short-term psychosocial stressor. Plasma levels of clotting factor VII activity (FVII:C), FVIII:C, fibrinogen, D-dimer, and catecholamines were measured at rest, immediately after stress, and 20 min and 60 min post-stress. The integrated change in D-dimer levels from rest to 60 min post-stress differed between medication groups controlling for demographic and metabolic factors (P = 0.047, eta(p)(2) = 0.195). Compared with the melatonin group, the placebo group showed a greater increase in absolute D-dimer levels from rest to immediately post-stress (P = 0.13; eta(p)(2) = 0.060) and significant recovery of D-dimer levels from immediately post-stress to 60 min thereafter (P = 0.007; eta(p)(2) = 0.174). Stress-induced changes in FVII:C, FVIII:C, fibrinogen, and catecholamines did not significantly differ between groups. Oral melatonin attenuated the stress-induced elevation in the sensitive coagulation activation marker D-dimer without affecting catecholamine activity. The finding provides preliminary support for a protective effect of melatonin in reducing the atherothrombotic risk with acute mental stress.

Identification of pathogen and host-response markers correlated with periodontal disease

BACKGROUND: Periodontitis is the major cause of tooth loss in adults and is linked to systemic illnesses, such as cardiovascular disease and stroke. The development of rapid point-of-care (POC) chairside diagnostics has the potential for the early detection of periodontal infection and progression to identify incipient disease and reduce health care costs. However, validation of effective diagnostics requires the identification and verification of biomarkers correlated with disease progression. This clinical study sought to determine the ability of putative host- and microbially derived biomarkers to identify periodontal disease status from whole saliva and plaque biofilm. METHODS: One hundred human subjects were equally recruited into a healthy/gingivitis group or a periodontitis population. Whole saliva was collected from all subjects and analyzed using antibody arrays to measure the levels of multiple proinflammatory cytokines and bone resorptive/turnover markers. RESULTS: Salivary biomarker data were correlated to comprehensive clinical, radiographic, and microbial plaque biofilm levels measured by quantitative polymerase chain reaction (qPCR) for the generation of models for periodontal disease identification. Significantly elevated levels of matrix metalloproteinase (MMP)-8 and -9 were found in subjects with advanced periodontitis with Random Forest importance scores of 7.1 and 5.1, respectively. The generation of receiver operating characteristic curves demonstrated that permutations of salivary biomarkers and pathogen biofilm values augmented the prediction of disease category. Multiple combinations of salivary biomarkers (especially MMP-8 and -9 and osteoprotegerin) combined with red-complex anaerobic periodontal pathogens (such as Porphyromonas gingivalis or Treponema denticola) provided highly accurate predictions of periodontal disease category. Elevated salivary MMP-8 and T. denticola biofilm levels displayed robust combinatorial characteristics in predicting periodontal disease severity (area under the curve = 0.88; odds ratio = 24.6; 95% confidence interval: 5.2 to 116.5). CONCLUSIONS: Using qPCR and sensitive immunoassays, we identified host- and bacterially derived biomarkers correlated with periodontal disease. This approach offers significant potential for the discovery of biomarker signatures useful in the development of rapid POC chairside diagnostics for oral and systemic diseases. Studies are ongoing to apply this approach to the longitudinal predictions of disease activity.

EGFR exon-level biomarkers of the response to bevacizumab/erlotinib in non-small cell lung cancer

Activating epidermal growth factor receptor (EGFR) mutations are recognized biomarkers for patients with metastatic non-small cell lung cancer (NSCLC) treated with EGFR tyrosine kinase inhibitors (TKIs). EGFR TKIs can also have activity against NSCLC without EGFR mutations, requiring the identification of additional relevant biomarkers. Previous studies on tumor EGFR protein levels and EGFR gene copy number revealed inconsistent results. The aim of the study was to identify novel biomarkers of the response to TKIs in NSCLC by investigating whole genome expression at the exon-level. We used exon arrays and clinical samples from a previous trial (SAKK19/05) to investigate the expression variations at the exon-level of 3 genes potentially playing a key role in modulating treatment response: EGFR, V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) and vascular endothelial growth factor (VEGFA). We identified the expression of EGFR exon 18 as a new predictive marker for patients with untreated metastatic NSCLC treated with bevacizumab and erlotinib in the first line setting. The overexpression of EGFR exon 18 in tumor was significantly associated with tumor shrinkage, independently of EGFR mutation status. A similar significant association could be found in blood samples. In conclusion, exonic EGFR expression particularly in exon 18 was found to be a relevant predictive biomarker for response to bevacizumab and erlotinib. Based on these results, we propose a new model of EGFR testing in tumor and blood.

Integrated reconstruction of Holocene millennial-scale environmental changes in Tierra del Fuego, southernmost South America

This study presents new paleoenvironmental data obtained from sedimentary cores from Lago Fagnano, an elon- gated lake located at 54°S in southernmost South America. Data from palynomorphs (pollen, spores and algae) and associated palynofacies as well as from diatom taxa retrieved from these cores compared with other regional proxies contribute to evaluate the similarities and differences in the climate patterns based on different proxies from southernmost Patagonia. The pollen analysis reveals that a grass steppe environment existed during the early Holocene (11,300–~8000 cal a BP) followed by a major vegetation change characterized by development of forest-steppe ecotone communities between ~8000 and ~6500 cal a BP, under more humid conditions. Between ~ 6500 and ~ 4000 cal a BP, expansion and colonization by Nothofagus forests reflect an increase in effec- tive moisture levels, while openness in the forest communities characterizes the region after ~ 1100 cal a BP. The palynological organic matter combined with the algal content reflects hydrological changes occurring in the lake and its nutrient status, probably in close relation with past climate oscillations. All these past ecological changes are closely related to oscillations in precipitation and temperature as a response to the variations in the latitudinal position and/or strength of the Southern Westerlies wind belt during the Holocene.

IMPROVING QUANTITATIVE TREATMENT RESPONSE MONITORING WITH DEFORMABLE IMAGE REGISTRATION

Quantitative imaging with 18F-FDG PET/CT has the potential to provide an in vivo assessment of response to radiotherapy (RT). However, comparing tissue tracer uptake in longitudinal studies is often confounded by variations in patient setup and potential treatment induced gross anatomic changes. These variations make true response monitoring for the same anatomic volume a challenge, not only for tumors, but also for normal organs-at-risk (OAR). The central hypothesis of this study is that more accurate image registration will lead to improved quantitation of tissue response to RT with 18F-FDG PET/CT. Employing an in-house developed “demons” based deformable image registration algorithm, pre-RT tumor and parotid gland volumes can be more accurately mapped to serial functional images. To test the hypothesis, specific aim 1 was designed to analyze whether deformably mapping tumor volumes rather than aligning to bony structures leads to superior tumor response assessment. We found that deformable mapping of the most metabolically avid regions improved response prediction (P<0.05). The positive predictive power for residual disease was 63% compared to 50% for contrast enhanced post-RT CT. Specific aim 2 was designed to use parotid gland standardized uptake value (SUV) as an objective imaging biomarker for salivary toxicity. We found that relative change in parotid gland SUV correlated strongly with salivary toxicity as defined by the RTOG/EORTC late effects analytic scale (Spearman’s ρ = -0.96, P<0.01). Finally, the goal of specific aim 3 was to create a phenomenological dose-SUV response model for the human parotid glands. Utilizing only baseline metabolic function and the planned dose distribution, predicting parotid SUV change or salivary toxicity, based upon specific aim 2, became possible. We found that the predicted and observed parotid SUV relative changes were significantly correlated (Spearman’s ρ = 0.94, P<0.01). The application of deformable image registration to quantitative treatment response monitoring with 18F-FDG PET/CT could have a profound impact on patient management. Accurate and early identification of residual disease may allow for more timely intervention, while the ability to quantify and predict toxicity of normal OAR might permit individualized refinement of radiation treatment plan designs.

Patient classification system: An integrated method for measuring nursing intensity and optimizing resource allocation

A patient classification system was developed integrating a patient acuity instrument with a computerized nursing distribution method based on a linear programming model. The system was designed for real-time measurement of patient acuity (workload) and allocation of nursing personnel to optimize the utilization of resources.^ The acuity instrument was a prototype tool with eight categories of patients defined by patient severity and nursing intensity parameters. From this tool, the demand for nursing care was defined in patient points with one point equal to one hour of RN time. Validity and reliability of the instrument was determined as follows: (1) Content validity by a panel of expert nurses; (2) predictive validity through a paired t-test analysis of preshift and postshift categorization of patients; (3) initial reliability by a one month pilot of the instrument in a practice setting; and (4) interrater reliability by the Kappa statistic.^ The nursing distribution system was a linear programming model using a branch and bound technique for obtaining integer solutions. The objective function was to minimize the total number of nursing personnel used by optimally assigning the staff to meet the acuity needs of the units. A penalty weight was used as a coefficient of the objective function variables to define priorities for allocation of staff.^ The demand constraints were requirements to meet the total acuity points needed for each unit and to have a minimum number of RNs on each unit. Supply constraints were: (1) total availability of each type of staff and the value of that staff member (value was determined relative to that type of staff's ability to perform the job function of an RN (i.e., value for eight hours RN = 8 points, LVN = 6 points); (2) number of personnel available for floating between units.^ The capability of the model to assign staff quantitatively and qualitatively equal to the manual method was established by a thirty day comparison. Sensitivity testing demonstrated appropriate adjustment of the optimal solution to changes in penalty coefficients in the objective function and to acuity totals in the demand constraints.^ Further investigation of the model documented: correct adjustment of assignments in response to staff value changes; and cost minimization by an addition of a dollar coefficient to the objective function. ^

Investigating Peatland Stratigraphy and Hydrogeology Using Integrated Electrical Geophysics

Hydrology has been suggested as the mechanism controlling vegetation and related surficial pore-water chemistry in large peatlands. Peatland hydrology influences the carbon dynamics within these large carbon reservoirs and will influence their response to global warming. A geophysical survey was completed in Caribou Bog, a large peatland in Maine, to evaluate peatland stratigraphy and hydrology. Geophysical measurements were integrated with direct measurements of peat stratigraphy from probing, fluid chemistry, and vegetation patterns in the peatland. Consistent with previous field studies, ground-penetrating radar (GPR) was an excellent method for delineating peatland stratigraphy. Prominent reflectors from the peat-lake sediment and lake sediment-mineral soil contacts were precisely recorded up to 8 m deep. Two-dimensional resistivity and induced polarization imaging were used to investigate stratigraphy beneath the mineral soil, beyond the range of GPR. We observe that the peat is chargeable, and that IP imaging is an alternative method for defining peat thickness. The chargeability of peat is attributed to the high surface-charge density on partially decomposed organic matter. The electrical conductivity imaging resolved glaciomarine sediment thickness (a confining layer) and its variability across the basin. Comparison of the bulk conductivity images with peatland vegetation revealed a correlation between confining layer thickness and dominant vegetation type, suggesting that stratigraphy exerts a control on hydrogeology and vegetation distribution within this peatland. Terrain conductivity measured with a Geonics EM31 meter correlated with confining glaciomarine sediment thickness and was an effective method for estimating variability in glaciomarine sediment thickness over approximately 18 km(2). Our understanding of the hydrogeology, stratigraphy, and controls on vegetation growth in this peatland was much enhanced from the geophysical study.

Taking personalized medicine seriously: Biomarker approaches in phase IIb/III studies in major depression and schizophrenia

The success rate in the development of psychopharmacological compounds is insufficient. Two main reasons for failure have been frequently identified: 1) treating the wrong patients and 2) using the wrong dose. This is potentially based on the known heterogeneity among patients, both on a syndromal and a biological level. A focus on personalized medicine through better characterization with biomarkers has been successful in other therapeutic areas. Nevertheless, obstacles toward this goal that exist are 1) the perception of a lack of validation, 2) the perception of an expensive and complicated enterprise, and 3) the perception of regulatory hurdles. The authors tackle these concerns and focus on the utilization of biomarkers as predictive markers for treatment outcome. The authors primarily cover examples from the areas of major depression and schizophrenia. Methodologies covered include salivary and plasma collection of neuroendocrine, metabolic, and inflammatory markers, which identified subgroups of patients in the Netherlands Study of Depression and Anxiety. A battery of vegetative markers, including sleep-electroencephalography parameters, heart rate variability, and bedside functional tests, can be utilized to characterize the activity of a functional system that is related to treatment refractoriness in depression (e.g., the renin-angiotensin-aldosterone system). Actigraphy and skin conductance can be utilized to classify patients with schizophrenia and provide objective readouts for vegetative activation as a functional marker of target engagement. Genetic markers, related to folate metabolism, or folate itself, has prognostic value for the treatment response in patients with schizophrenia. Already, several biomarkers are routinely collected in standard clinical trials (e.g., blood pressure and plasma electrolytes), and appear to be differentiating factors for treatment outcome. Given the availability of a wide variety of markers, the further development and integration of such markers into clinical research is both required and feasible in order to meet the benefit of personalized medicine. This article is based on proceedings from the "Taking Personalized Medicine Seriously-Biomarker Approaches in Phase IIb/III Studies in Major Depression and Schizophrenia" session, which was held during the 10th Annual Scientific Meeting of the International Society for Clinical Trials Meeting (ISCTM) in Washington, DC, February 18 to 20, 2014.