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All body functions can be viewed from an evolutionary standpoint. The ability to sense physical pain is extremely important in order to survive, signal injury to the brain, avoid further injury, and to give the affected body part enough time to heal. Acute pain usually comes on suddenly and is caused by something specific. It is sharp in quality. Acute pain goes away when there is no longer an underlying cause for the pain, and usually does not last longer than six months. After acute pain subsides, people can go on with their life as usual.
Causes of acute pain include:
- Dental work
- Broken bones
- Burns or cuts
Chronic pain is pain that is ongoing and usually lasts longer than six months. This type of pain can continue even after the injury or illness that caused it has long healed or gone away. Defective pain signalling mechanisms remain active in the nervous system and brain for weeks, months, or years. Some people suffer chronic pain even when there is no past injury or apparent body damage. People who have chronic pain can have physical effects that are stressful on the body. These include tense muscles, limited ability to move around, a lack of energy, and appetite changes. Emotional effects of chronic pain include depression, anger, anxiety, and fear of re-injury. Such a fear might limit a person’s ability to return to their regular work or leisure activities.
Chronic pain can be linked to conditions including:
- Back pain
- Headache and migraines
- Intense physical and/or emotional traumatisation
- Nerve pain
- Persistent post-surgical pain (PPSP)
Quantitative systems pharmacology (QSP) is an approach that uses computational and mathematical models to describe dynamic interactions between a drug and the pathophysiology to understand the biological system (body) at the cellular and biochemical network levels. QSP modelling aims to improve the understanding of the body and how it is changed by the disease, facilitates early and more thorough in silico testing of drug candidates, supports rational decision making, and reduces the costs and time of de novo drug development. QSP combines mechanistic modelling of disease pathophysiology, a systemic (whole-body) approach, the pharmacokinetics (PK, which is what the body does with the drug) and pharmacodynamics (PD, which is what the drug does with the body) of a therapeutic agent, and quantitative experimental data. The resulting model can be used to run simulations, beyond of what is currently known, to understand how drugs modify cellular networks, for example in neuronal networks in the brain, and how they are impacted by the pathophysiology, the significant pathways, drug parameters, biological variance, and drug efficacy and safety.
QSP is increasingly used in drug discovery and development to guide research and decision making on areas such as:
Dose optimization: Complex diseases such as cancer, diseases of the central nervous system (e.g. chronic pain), and metabolic diseases typically involve combination therapy. Incorporating disease mechanisms via QSP models leads to important and often counterintuitive insights for deciding optimum dose levels and combination therapy approaches.
Precision medicine: Many diseases but also many medications exhibit heterogeneity, meaning the subpopulations of patients are affected differently. The use of QSP models can incorporate the impact of biological variance on efficacy and safety and lead to rational decisions on which patient subpopulation to treat with which treatment paradigm.
Target feasibility and selection: Designing a therapeutic agent often starts with choosing from a list of potential candidates. Developing QSP models for each potential target leads to establishing affinity and dose requirements and predicting optimal drug parameters early on. This approach helps eliminate less promising drug targets, so one can pursue more promising candidate drugs.
Drug efficacy and safety: Most drugs fail in the clinical trial stage because of low efficacy. High efficacy levels in animal experiments often do not translate to humans. QSP models have the potential to predict this behaviour. In addition to predicting which drugs will be more efficient, QSP can help identify which drugs might fail and for which reasons. Because QSP models can predict drug exposure at the organ and systems biology level, they also provide insights into the mechanism of toxicity and potential side effects.
QSPainRelief is an acronym of the full project title and the research consortium’s leading objective, namely “Effective combinational treatment of chronic pain in individual patients by an innovative Quantitative Systems (QSP) Pharmacology pain relief approach”. In order to pursue this objective, QSPainRelief has set itself five key goals:
- The first goal is to develop a computational platform that identifies novel combinations of existing medications in a cost-effective manner. The most promising in silico-identified combinational treatment paradigms will then be validated in preclinical animal studies and in stratified patient groups, according to each patient’s genetic background, personal disease history, and individual needs.
- The second goal is to deepen the scientific understanding of the underlying physiological mechanisms of both the pathophysiology of chronic pain as well as the best possible analgesia to improve pain relief while reducing side effects to a minimum.
- The third goal is to better understand the influence of individual differences, such as age, sex and gender, genetic predisposition, causal diseases, and comorbidities regarding the efficacy of analgesic treatments to be able to stratify patients properly and personalise and improve pain treatment for individual patients.
- The fourth goal is to communicate research results frequently, clearly, and widely to affected individuals, patient organisations, scientists, and the general public, and to develop clinical guidance documents for health care providers, health insurance agencies, policymakers, and regulators. The latter is absolutely crucial to generate real-life impact in improving the quality of life for chronic pain patients.
- The fifth goal is of direct socioeconomic nature, namely to increase innovative research opportunities. Since four small and medium-sized enterprises (SMEs) are key partners within QSPainRelief, this objective has been already partially met.
Expected impacts of QSPainRelief that will create direct benefits for chronic pain patients are:
- The development and implementation of novel and improved combinational treatment strategies in clinical practice
- A higher treatment efficacy due to personalised medicine and effective patient stratification
- Improved acceptance of combinational therapies in the clinical setting
- Reduced stigmatisation of chronic pain as a health condition through improved and clear communication to and with the general public
Dr. Geert Jan Groeneveld
CSO and CMO at CHDR
+31 715 246 407
Healthy volunteers will be recruited via media advertisement or from the subjects’ database of the Centre for Human Drug Research (CHDR), Leiden, Netherlands. Whenever a volunteer shows interest in participating, he/she will be asked to join an information session that will take place at CHDR, prior to giving informed consent. During the information session, detailed information about the study and informed consent forms will be distributed by the research team of the CHDR.
Note: The healthy status is defined by the absence of evidence of any active or chronic disease following a detailed medical and surgical history questionnaire, a complete physical examination including vital signs, an electrocardiogram (ECG), haematology, blood chemistry, and urine analysis.
Main inclusion criteria are:
- 18 to 45 years of age
- Body mass index (BMI) between 18 and 30 kg/m2 (minimum weight 50kg, maximum weight 100kg)
- Able to participate and willing to give written informed consent and to comply with the study restrictions
Prof. Dr. Patricia Lavand’homme
Professor of Anaesthesiology
Phone: +32 276 418 97
Patients will be recruited through the transitional post-surgical pain consultation headed by Prof. Patricia Lavand’homme at the Cliniques Universitaires Saint-Luc (CUSL) in Brussels, Belgium. Whenever a patient shows interest in participating, he/she will be contacted by the principal investigator or a co-investigator to receive detailed information about the study prior to giving written informed consent.
Important: Deciding whether or not to take part in the study will have no impact on patient care. Regardless of participation, patients will receive the accepted best available treatment as defined by the caregivers. Travel expenses for the patients will be reimbursed.
Main inclusion criteria are:
- Aged 18-70 years
- Presence of disabling post-operative pain for more than two weeks following thoracotomy, breast cancer surgery, inguinal hernia repair or spine surgery
- Current treatment of their post-operative pain with an opioid (along with possible other drugs)
- Decision by the treating physician to introduce one of the following non-opioid for the treatment of their post-operative pain: an antiepileptic (e.g. pregabalin), an antidepressant (e.g. amitriptyline, nortriptyline, duloxetine), a benzodiazepine, or an alpha2-agonist (e.g. clonidine)
- Capacity to understand and voluntarily sign an informed consent form
- Normal laboratory assessment of renal and hepatic function (assessed using available clinical biological tests)
Processing of patient data for research within QSPainRelief underlies strict ethics guidelines for data protection. Therefore, patient data will only be used after an explicit written agreement, so-called informed consent, by each patient and in an untraceable anonymized way.
What do you want to know about QSPainRelief? Send us your questions!
Prof. Dr. Liesbeth de Lange (Scientific Coordinator)
Dr. Nina Donner (Dissemination Manager)
Dr. Sara Stöber (Project Manager)