✅ M3 - Precision Medicine Flashcards
What are the different definitions and uses of medicine?
- Personalised medicine: an approach to both preventative care and drug therapy that is based on the individual’s genetic & other relevant information
-> downside: purely for that person (not that specific) - Precision medicine: tailoring of medical treatment to the individual characteristics of each patient, usually involving patients being classified into subpopulations
-> patient is not a completely distinct individual - P4 medicine: predictive, preventative, personalised, and participatory medicine
-> patient also involved in the decision (not from doctors only)
What is the difference in approaches between traditional and precision medicine?
- Traditional approach: “one size fits all” drug prescribed for “typical” patient (e.g. pre-made suit) => BUT not successful for everyone, genetically and environmentally different
- Move to Precision medicine: “specific drugs with personalised quantity and treatment frequency” (e.g. bespoke suit) => BUT very expensive
What is the history/origin of precision medicine?
The idea is not new
1902: family line inheritance of alkaptunoria (rare disease) -> needs personalised treatment
1956: discovered genetic basis of selective toxicity of primaquine, an anti-malarial drug
1977: discovered role of cytochrome p450 metabolising enzyme variations in overdose toxicity (some variations tolerate/react better to drugs)
2003: finish of human genome project
What is biomarker & how is it related to the development of precision medicine through human genome project?
Biomarker: a naturally occurring molecule, gene, or characteristic by which a particular pathological or physiological process, disease, etc. can be identified.
=> We advance by using biomarker
Pharmacogenomics (PGx): a field of study that looks at how a person’s genes affect their response to drugs.
- At start: only know 4 drugs with (PGx) info.
- Now: 261 drugs with PGx info, 363 drug - biomarker pairs
What are the changes we are looking for to create precision medicine?
- Generally anything in the body (e.g. function, expression, interaction, physiological measurement, etc.) that informs a change between pre-diagnosis and post-diagnosis.
- We can obtain information from tests, such as:
1. Genomics (genetic material)
2. Transcriptomics (active gene)
3. Proteomic (protein)
4. Lipidomics (fat-related molecules)
5. Metabolomics (small molecules in body)
6. Epigenomics (gene control)
How do biomarkers informs disease & its progression?
6 key-steps of disease progression (an overview)
- Presence of a disease (presence of biomarker which commonly appears in patients)
- Risk of developing a disease (biomarker presence/absence risk factor of disease onset)
- Prognosis (risk of recurrence & inheritance)
- Predictive (patients’ future responses to treatment)
- PGx (find out reaction to drugs)
- Monitoring treatment response (amount of biomarker)
Examples of how biomarker informs disease & its progression”? [1]
- Presence of a disease: diagnosis of prostate cancer using PSA (prostate-specific antigen)
- PSA can be high for multiple reasons -> false positives
- Low specificity (not certain)
- Requires further tests to confirm diagnosis (e.g. biopsy) -> stress, costs, and risks of infection - Risk of developing a disease: predicting likelihood of breast and ovarian cancers (mutation of BRCA1 or BRCA2 gene)
- Using BRAC analysis
- positive for mutation -> 85% lifetime chance of breast cancer, 60% for ovarian cancer
- negative for mutation -> 13% lifetime chance of breast cancer, 0.7% for ovarian cancer
Examples of how biomarker informs disease & its progression”? [2]
- Prognosis (disease progression): help determine risk of recurrence and aid in treatment decision.
- Utilise a number of biomarkers
- E.g. 70-gene risk of recurrence signature - Predictive (patients’ future responses to treatment): targeting therapy based on molecular diagnosis & drug-biomarker pairing
- 25-30% patients with breast cancer are HER2 positive
- over-expression of HER2 cell-surface receptor -> lead to abnormal cell growth
- Drug developed + chemotherapy => 52% reduction in re-occurrence of tumour (than just chemo alone)
- Requires high selectivity & specificity of cause
- Issue with sensitivity in the type of test used (to measure expression of HER2)
Examples of how biomarker informs disease & its progression”? [3]
- PGx (find out reaction to drugs): improve dosing, efficacy & reducing side/adverse effects:
- Liver metabolising enzyme mutations (drug-breakdown enzyme) -> specific to drugs
- Lots of mutations (thousands)
- Types:
+ slow metabolisers -> overdose toxicity
+ normal metabolisers
+ fast metabolisers
+ ultra fast metabolisers: drug does not work
=> e.g. prevent-blood-clot drugs for stent patients - Monitoring treatment response:
- identify expression of Ki67 in tumour cell growth
- if treatment is working -> reduction in Ki67 as indication
- but more invasive (requires biopsy to analyse)
What are the 3 benefits of biomarkers and precision medicine?
- Some allow changing lifestyle -> reduce disease risk onset
- Some allow early decision-making (BRCA 1&2)
- Some aid drug development
- reduces cost, attrition rate and time of development
- stratifying patients for clinical trials -> change how clinical trials are carried out
- easier to pick up effect in same mutation group
- improves chance of positive outcomes rather than negative
Other applications of precision medicine?
(NOT just genes and drugs)
- Tinnitus masker: white noise player for hearing disruption
- Software-based quantitative EEG analysis: looking at brain wave for diagnosis
- Artificial pancreas device system: personalised diabetic treatments
- Custom made splints: repair poorly developed organ/body parts
What are some controversies over precision medicine?
- Ethics:
- Concerns over genome data protection and privacy
- Concerns over false diagnosis - Gene mutations/variations:
- Too many mutations
- May not correctly identified main gene that causes specific disease - Genomic statistic:
- How do we cope with handling large amount of data?
- Implications for AI - Does it work?
- Works for some, but not all
- Expensive but uncertain (wasted effort)
What is meant by ‘direct to consumer’ tests?
- Usually require a biological specimen (eg. saliva) which is then sent to company for analysis
- The specimen tested can reveal:
- Microbiome
- Toxins in body
- Ancestry (DNA)
- Prediction of disease risk - Example: 23 & Me -> very popular for people to test their genetic material & find out about themselves
What is the history (timeline) of 23 & me?
2007: launched, first company to offer autosomal DNA ancestry testing
2013: stopped personal genome service in US but still offer ancestry service (ethical implication)
2014: launched in Canada and UK (different regulations)
2015-2018: FDA approved numerous “disease-carrier” tests (no longer testing for full genome)
2018: partnerships with different pharmaceutical companies
- GSK: allowed sharing of personal data
- Using genome information to find patients carrying disease to develop new drugs in clinical trial (2020) -> ethical? (data leak risk)
2021: Merged with Richard Brandson’s VG Acquisition Corp.
What are we trying to detect by using this service?
- Trying to detect a target or multiple targets that tell us about the disease
- Help with prediction, cause, diagnosis, progression, regression, or outcome of treatment of disease
- Where do we detect these biomarkers?
- Any part of the body where we can look at protein, DNA, cell, for examples:
- Tissue (normal or diseased)
- Blood (most common for testing disease)
- Saliva (ancestry test)
- Sweat
- Hair (test for toxins)