PHARMACODYNAMICS & -KINETICS
LE: PERSONALIZED HEALTHCARE
ROLE OF MOLECULAR (OMICS) BIOMARKER DATA IN PERSONALIZED HEALTHCARE
Vicious circle of patient → X-omics → personalized healthcare (= personalized diagnosis, therapy and
participation) → therapy monitoring → patient
PERSONALIZED HEALTHCARE IN RARE METABOLIC DISEASES
Diagnosis:
- Genetic screening: tri whole exome sequencing (mother, father, child)
- Metabolic screening: e.g. urine analysis
→ genetic metabolic disorder = inborn errors of the metabolism
e.g. Uridine monophosphate synthase (UMPS) deficiency:
- personalized diagnosis: high orotic acid
- personalized therapy: uridine supplementation
- however: route to therapeutic drug difficult (import, insurances)
o alternative: food supplementation @ local drug store
Lessons learned:
- on personal diagnosis: technology innovation is driving impact in personalized healthcare &
combination of genetic and metabolic screening is a strong approach towards identifying mechanism
of disease
- on personalized medicine: impressive effect of uridine therapy, increase quality of life for patient and
family & frequent issues regarding expensive medication vs cheap supplements
Other story: personalized healthcare in multiple myeloma
- 2nd most common haematological malignancy
- Monoclonal plasma cells in bone marrow that secrete a M protein
- Treated by chemo, steroids and specific drugs
- ~50% of patients achieve minimal residual disease (MRD)
- Need to restart therapy as soon as disease relapses
- Diagnostic test for MM: blood M-protein gel electrophoresis
- Current test for MRD: isolate bone marrow, analysis stromal cells by flow cytometry or genomics (PCR,
NGS)
o Problems: cumbersome and invasive procedure for repetitive monitoring & sampling error
caused by tumour heterogeneity
o Can we use plasma proteomics to monitor MRD?
▪ Approach: direct measurement of rearranged region of the M-protein targeted
proteomics in plasma samples (= MS MRD method)
• Mass spectrometry strongly increases sensitivity detection M-protein as it is
feasible for monitoring and early detection relapses & re-analysis of
archived gels possible
▪ Parallel reaction monitoring (PRM)
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, o Conclusion: sequencing-MRD vs mass spectrometry-MRD: similar sensitivity & perform
equally well as prognostic marker
Lessons learned:
- Technology innovation is driving impact in personalized healthcare
- Analysis of dynamic biomarkers is key in monitoring Minimal Residual Disease to:
- Mass spectrometry has added value and good potential here
- Collaboration between clinic, lab specialists, proteomics labs + between academics and industry is
needed and works!
o Analytical development
o Clinical validation
Clinical omics data to drive personalized healthcare: personalized analysis → diagnosis of (new)
disease mechanisms → initiation and monitoring of (new) personalized therapies
DIGITAL BIOMARKERS
e.g. smartwatch, minion, etc
Advantages digital biomarkers
- Continuous monitoring versus 1 snapshot observation
- Real world data versus data from clinically controlled circumstances
- More comprehensive and rich data sets
- Truely personalized
- Strong potential in molecular + clinical + digital + environmental biomarkers for optimal insight in
complex biological systems
- Better basis to drive Personalized health(care)
- Better support for phase 1, 2, 3, 4 clinical trials
Digital biomarkers enable personalized health monitoring: past (population) → present (subgroups) → future
(individual data through self-monitoring)
Wearables: personalized Parkinson project
- Bas Bloem, The personalized Parkinson Project: examining disease progression through broad
biomarkers in early Parkinson’s disease
o Verily study watch: Scheduled tasks: e.g. seated rest, hand opening
o Enables frequent and reliable remote measurements of motor function
Personalized health(care) model
- Primary prevention: avoiding disease
- Secondary prevention: screening to identify
disease the earliest
- Tertiary prevention: managing disease post
diagnosis to stop or slow
A personalized data-driven GPS for health
- Monitor on background
- Alert when you are at risk
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, - Advice what to do, Doctor as coach?
3 INNOVATION GAPS
- Research to research
- Research to clinic
o Numerous biomarkers are discovered → only few being validated/confirmed → only fewer
being diagnostic tested (whole pathway takes a lot of time)
▪ Also goes for the digital markers, e.g. smartphone app detects bacteria/diseases
o Also quality issues in commercial health biomarker analysis, e.g. 23andMe ‘post-traumatic
test syndrome’ of medical advice falsely given by the company
- Research to society
Big hopes for big data, but.. crap data will remain crap data even if mare FAIR (findable accessible
interoperable reusable) and AI-ready
- Publication bias: the failure to publish the results of a study on the basis of the direction or strength of
the study findings.
- Funding bias: the tendency of a scientific study to support the interests of the study's financial
sponsor.
Choice for scientists: discover or confirm?
Most importantly: always focus on the end user: patient/citizen
➔ Big debate about ethical, legal, societal aspects
Afterthought: there is no single reflection of health
- ‘Funhouse mirror effect’: everything reflects you
- Multiple sources of your data
o Clinical chemistry
o Omics analyses
o Digital biomarkers/ wearables
o Self-testing health checks
o Social media
o Surrounding
- Each are a skewed image of you
- How to deal with all of this for your personal health(care)
LE: PHARMACODYNAMICS AND PHARMACOKINETICS
- Everything is poison depending on the dose (Paracelsus)
- Pharmacology = the science that is concerned with the uses, effects and modes of action of chemicals
on the function of living systems
- There are different levels to pharmacology: molecule, cell, organ, organism, family, population →
Pharmacotherapy focusses on patients
PHARMACOTHERAPY
- What does the patient do with the drug: pharmacokinetics; e.g.
- What does the drug do with the patient: pharmacodynamics; e.g. binding to target and changing the
receptor
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, ➔ Together they form rational pharmacotherapy
‘mechanism-based pharmacotherapy’ (=Rational pharmacotherapy) vs ‘evidence-based pharmacotherapy’ (= it
does not matter how it works, as long as it works, e.g. paracetamol)
Pharmacological phases in pharmacotherapy
Dosis
- Exposition phase: behaviour of a substance in the environment, changes in the application form,
available for uptake.
- Toxicokinetic phase: Absorption, distribution, biotransformation (toxification, detoxification),
excretion. ADME
- Toxicodynamic phase: Interactions with receptors or other (macro) molecules at the site of the
operation
Effect
DRUG-RECEPTOR-INTERACTIONS
Types of interactions
- Ligand-gated ion channels (ionotropic receptors
- G-protein-coupled receptors (metabotropic)
- Kinase-linked receptors
- Nuclear receptors
➔ Think of the type of rection you need when choosing pathway
Binding sites
- Receptors: agonist, antagonist
- Ion channels: blockers, modulators
- Enzymes: inhibitor, false substrate, pro-drug
- Transporters: normal transport, inhibitor, false substrate
Different types of binding: covalent, ionic, hydrogen, hydrophobic, van der waals
e.g. monarch butterfly is toxic to humans as the larvae sequester toxic steroids, known as cardenolides, from
milkweed → ouabain/digoxine also used as medicine → binds to the NA,K-ATPse receptor
RELATION CONCENTRATION – RECEPTOR OCCUPATION
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