Background: Concise methodological directions for administration of serial cardiopulmonary exercise testing (CPET) are needed for testing of patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). Maximal CPET is used to evaluate the coordinated metabolic, muscular, respiratory and cardiac contributions to energy production in patients with ME/CFS. In this patient population, CPET also elicits a robust post-exertional symptom flare (termed, post-exertional malaise); a cardinal symptom of the disease. CPET measures are highly reliable and reproducible in both healthy and diseased populations. However, evidence to date indicates that ME/CFS patients are uniquely unable to reproduce CPET measures during a second test, despite giving maximal effort during both tests, due to the effects of PEM on energy production.Methodology: To document and assess functional impairment due to the effects of post-exertional malaise in ME/CFS, a 2-day CPET procedure (2-day CPET) has been used to first measure baseline functional capacity (CPET1) and provoke post-exertional malaise, then assess changes in CPET variables 24 h later with a second CPET to assess the effects of post-exertional malaise on functional capacity. The second CPET measures changes in energy production and physiological function, objectively documenting the effects of post-exertional malaise. Use of CPET as a standardized stressor to induce post-exertional malaise and quantify impairment associated with post-exertional malaise has been employed to examine ME/CFS pathology in several studies. This article discusses the results of those studies, as well as the standardized techniques and procedures for use of the 2-day CPET in ME/CFS patients, and potentially other fatiguing illnesses.Conclusions: Basic concepts of CPET are summarized, and special considerations for performing CPET on ME/CFS patients are detailed to ensure a valid outcome. The 2-day CPET methodology is outlined, and the utility of the procedure is discussed for assessment of functional capacity and exertion intolerance in ME/CFS.

Physiomics and pharmacometrics have collaborated to design a new database of anti-cancer drugs and therapeutic treatment information aimed at researchers in oncology and clinicians. This database, accessible through the web, offers data on more than 130 anti-cancer drugs (small molecules and biologics) used in research and in the clinic. It contains information on drug combination as well as a several hundreds of cancer chemotherapy regimens routinely used in the clinic. These data are classified according to tumor type, species, or source (in vitro, in vivo or simulated). It will be constantly expanded and curated with the most recent information. Furthermore, it provides ways to standardize the expression and nomenclature of chemotherapy regimens unambiguously and uniformly is of paramount importance to improve efficacy, as well as to reduce medication errors. Individual drug information covers pharmacokinetic profiles, mechanism of action and of resistance, dose-response effect, dosing limits, therapeutic index, and immunosuppression data. Drug combinations are also referenced. The database covers synergy or antagonism, as well as a combination therapeutic index and cross-resistance information. Some drug combination having level of synergy depending on the drug schedule, drug sequence and administration timings are also referenced and thoroughly discussed. The user can also browse and compare chemotherapeutic regimens, analyze the overall drug dose over a course of treatment, by tumor type, in animal and clinical models. Advanced functions include the ability to do statistical analysis on drug usage and dosing in various contexts. It can also help determine which drug candidates are likely to be used in combination with a new chemical or biological entity, given the mechanism of action and other PK/PD data. Also, it will allow users to design new combinations and regimens, which obey dosing constraints, such as MLD and MTD. Finally, data can be exported and used in spread sheets, modeling software or simulation packages. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr A36.

Physiomics and Pharmacometrics have collaborated to design a new database of anti-cancer drugs and therapeutic treatment information. The objective is to provide a database of anti-neoplastic agents, regimens and combinations for use by clinicians and researchers in oncology. The drugCARD database, accessible through the web, offers data on more than 130 anti-cancer drugs (small molecules and biologics) used in research and in the clinic. It contains information on drug combinations as well as several hundreds of cancer chemotherapy regimens used routinely in the clinic. The data are classified according to tumour type, species and experimental system (in vitro or in vivo). This database will be regularly expanded and curated with the most current information. Individual drug information contained within the database comprises pharmacokinetic profiles, mechanisms of action and resistance, dose-response effect, dosing limits, therapeutic index and immunosuppression data. Drug combinations are also referenced. The database covers synergy or antagonism, and includes the combination therapeutic index and cross-resistance information. Drug combinations where the level of synergy is dependent upon the drug schedule, drug sequence or administration timing are also referenced and thoroughly discussed. The user can browse and compare chemotherapeutic regimens, and analyse the overall drug dose over a course of treatment, by tumour type, in animal and clinical models. Moreover, the database enables users to design new combinations and regimens that obey dosing constraints (such as MLD and MTD), and can be used to determine drug candidates that could be combined with a new chemical or biological entity, given the respective mechanisms of action and other PK/PD data. Data can be exported for analysis in spreadsheets, modelling software or simulation packages. Advanced functions will include the ability to carry out statistical analysis on drug usage and dosing in various contexts. Finally, the database allows the expression and nomenclature of chemotherapy regimens to be standardized, which is of paramount importance in improving efficacy, as well as reducing medication errors (Kohler et al 1998). Citation Format: Eric Fernandez, Jianxiong Pang, Chris Snell, Cathy Derow, Frances Brightman, Christophe Chassagnole, Robert Jackson. drugCARD: a database of anticancer treatment regimens and drug combinations. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5147. doi:10.1158/1538-7445.AM2013-5147