Biotechnology in Medicine
5. Personalized Medicine
Learning outcomes
- I can define personalized medicine.
- I can explain how genetic information can guide treatments.
- I can describe the role of DNA analysis in healthcare.
- I can identify benefits of personalized medical approaches.
- I can evaluate challenges associated with personalized medicine.
For much of medical history, patients with the same disease were often treated in broadly similar ways. However, people are biologically different, and the same treatment may work very well for one person but less well for another.
Personalized medicine—often called precision medicine—uses information about an individual or a specific disease to help guide prevention, diagnosis, and treatment.
This information can include:
- genetic variation
- characteristics of a tumour or pathogen
- age
- environment
- lifestyle
- medical history
- laboratory results
- response to previous treatments
Genetics is therefore an important part of personalized medicine, but it is not the only part.
What Is Personalized Medicine?
Personalized medicine is an approach that uses biological and other relevant information to help tailor healthcare decisions to individuals or groups of patients with particular characteristics.
Instead of assuming:
same disease → same treatment for everyone
personalized medicine asks:
What characteristics of this patient or disease could help us choose the most appropriate treatment?
A simplified pathway is:
patient
↓
clinical + biological information collected
↓
relevant differences identified
↓
treatment options compared
↓
treatment selected
↓
response monitored
↓
treatment adjusted if necessary
Why Are People Different?
Humans share the vast majority of their DNA sequence, but individuals also have millions of genetic differences.
Some genetic variants have little or no noticeable effect.
Others can influence:
- physical characteristics
- disease susceptibility
- metabolism
- immune responses
- how medicines are processed
- responses to particular treatments
Personalized medicine attempts to use medically relevant differences rather than treating every patient as biologically identical.
Genetic Variation
A genetic variant is a difference in a DNA sequence.
For example, imagine the same region of DNA in three people:
Person A: ACGTAGCT
Person B: ACGTGGCT
Person C: ACGTAGCT
Person B has a different nucleotide at one position.
A single-base difference such as this can be called a single nucleotide variant (SNV).
Some common single-base variants are also called single nucleotide polymorphisms (SNPs).
Most such differences are harmless, but some can have medical significance.
From DNA to Health
Recall the basic relationship:
DNA → RNA → protein → cell function
A genetic variant can sometimes change:
- how much protein is produced
- the structure of a protein
- how well a protein functions
- when a gene is expressed
This can influence how the body responds to a medicine.
For example:
genetic variant
↓
different enzyme activity
↓
drug processed differently
↓
different drug concentration
↓
different treatment response
This is one reason DNA information can sometimes help guide medical decisions.
DNA Analysis
DNA analysis involves examining genetic material to identify relevant genetic information.
Depending on the purpose, scientists may examine:
- one gene
- several genes
- selected genetic variants
- the protein-coding regions of many genes
- much or nearly all of a genome
The appropriate test depends on the medical question.
Testing one specific variant may be sufficient in one situation, while a broader analysis may be needed in another.
A Simplified DNA-Analysis Process
A genetic test might involve:
patient sample collected
↓
DNA extracted
↓
DNA analyzed or sequenced
↓
genetic variants identified
↓
variants interpreted
↓
clinically relevant information reported
↓
healthcare decisions considered
Possible samples can include:
- blood
- saliva
- cheek cells
- tissue samples
- tumour biopsies
DNA Sequencing
DNA sequencing determines the order of nucleotides in DNA.
The four DNA bases are:
A – adenine
T – thymine
C – cytosine
G – guanine
Modern sequencing technologies can examine enormous amounts of DNA.
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Scientists can compare a patient's sequence with reference sequences and databases to identify variants that may have medical significance.
Gene Panels
Sometimes doctors are interested in a group of genes associated with a particular condition.
A gene panel examines selected genes.
For example, a cancer-related panel might investigate genes involved in:
- cell division
- DNA repair
- tumour growth
- signalling pathways
Gene panels provide a targeted approach.
They generate less information than sequencing an entire genome, which can make interpretation more manageable.
Whole-Exome Sequencing
The exome consists mainly of the protein-coding regions of genes.
These regions make up only a small fraction of the entire human genome, but many known disease-causing variants occur in protein-coding sequences.
Whole-exome sequencing (WES) examines much of this protein-coding information.
It can be useful when doctors suspect a genetic disorder but do not know which particular gene is involved.
Whole-Genome Sequencing
Whole-genome sequencing (WGS) examines most of a person's DNA.
This can provide extensive information about genetic variation.
However, more information also creates challenges.
Scientists may discover:
- clearly important variants
- harmless variants
- variants whose significance is uncertain
- unexpected findings unrelated to the original reason for testing
Producing sequence data is only one part of the problem.
Interpreting the data correctly is often much harder.
Variant Interpretation
Suppose sequencing finds a DNA variant.
Does that automatically mean the variant causes disease?
No.
Researchers must ask:
- Is the variant common?
- Has it been found in people with the disease?
- Does it change a protein?
- Does laboratory evidence show an effect?
- Does it occur in affected family members?
- What do previous studies show?
A variant may be classified as:
- pathogenic
- likely pathogenic
- uncertain significance
- likely benign
- benign
depending on the evidence and the classification framework being used.
Variants of Uncertain Significance
A variant of uncertain significance (VUS) is a genetic difference for which there is not enough evidence to determine whether it contributes to disease.
This is an important limitation of genetic testing.
Imagine sequencing identifies:
Variant X
but researchers do not yet know whether Variant X:
causes disease
or
is harmless
The test has produced information, but not necessarily a clear answer.
Pharmacogenomics
One important application of personalized medicine is pharmacogenomics.
Pharmacogenomics studies how genetic differences influence responses to medicines.
Genes can affect proteins involved in:
- drug metabolism
- drug transport
- drug targets
- immune reactions
Genetic information can sometimes help doctors predict how a patient may respond to particular medicines.
Drug Metabolism
After a medicine enters the body, it may need to be chemically modified.
The liver contains many enzymes involved in this process.
Genetic variation can influence how active some of these enzymes are.
Imagine two patients receive the same dose.
Patient A
Processes the drug relatively quickly.
Patient B
Processes it relatively slowly.
The same dose could potentially produce different drug concentrations in their bodies.
Therefore:
same medicine + same dose ≠ always same response
A Simplified Example
Suppose a medicine is normally broken down by Enzyme X.
Patient A
Produces highly active Enzyme X.
The drug is removed relatively quickly.
Patient B
Produces a less active form.
The drug remains in the body longer.
If both receive the same dose, Patient B could potentially experience a higher exposure to the drug.
Genetic information about Enzyme X could therefore help guide treatment in some circumstances.
Genes Can Affect Drug Activation
Some medicines are given in an inactive or less-active form and must be converted into an active compound inside the body.
These are sometimes called prodrugs.
Imagine:
Drug A → Enzyme Y → Active Drug B
If a patient's version of Enzyme Y has very low activity:
Drug A → little Active Drug B
The treatment may not work as expected.
Pharmacogenomic testing can sometimes help identify such differences.
Genes and Adverse Drug Reactions
Genetic differences can also influence the likelihood of particular adverse reactions.
For some medicines, genetic testing can help identify people who have a higher risk of a serious reaction.
This may allow clinicians to:
- choose another medicine
- adjust treatment
- increase monitoring
Personalized medicine can therefore help with both:
effectiveness
and
safety.
Personalized Cancer Treatment
Cancer is one of the most important areas of precision medicine.
Cancer develops when cells acquire genetic and other molecular changes that alter their growth and behaviour.
Different patients can have cancers in the same organ but with different molecular characteristics.
For example:
Patient A: lung cancer with Mutation X
Patient B: lung cancer without Mutation X
Even though both cancers began in the lung, they may respond differently to a treatment targeting the protein affected by Mutation X.
Tumour DNA
Cancer cells accumulate genetic changes.
Scientists can analyze DNA from a tumour sample to identify some of these changes.
A simplified pathway is:
tumour biopsy
↓
DNA extracted
↓
genetic analysis
↓
important tumour alterations identified
↓
possible targeted treatments considered
This approach is sometimes called molecular profiling.
Targeted Therapy
A targeted therapy is designed to interfere with a particular molecule or pathway involved in disease.
For example:
mutation → overactive protein → uncontrolled cell division
A drug may be designed to inhibit that protein.
The logic becomes:
identify molecular abnormality
↓
find treatment targeting abnormality
↓
treat selected patients
This can be more precise than choosing treatment solely according to where the cancer originated.
Biomarkers
A biomarker is a measurable biological characteristic that provides information about health, disease, or response to treatment.
Biomarkers can include:
- DNA variants
- RNA molecules
- proteins
- hormones
- cell-surface molecules
- metabolic products
A biomarker may help doctors:
- diagnose disease
- classify disease
- estimate risk
- select treatments
- monitor treatment response
Personalized medicine therefore extends beyond DNA alone.
Hereditary vs Acquired Genetic Changes
An important distinction in personalized medicine is between:
Germline Variants
Present in the egg or sperm that formed the individual and therefore generally found throughout the person's body.
These can sometimes be inherited.
Somatic Variants
Develop during a person's lifetime in particular cells.
Cancer cells commonly contain somatic mutations.
A mutation found in a tumour therefore does not automatically mean the mutation was inherited.
Personalized Medicine and Disease Risk
Genetic information can sometimes help estimate a person's risk of developing particular diseases.
For example, certain genetic variants are associated with increased risks of some cancers or inherited disorders.
However:
increased genetic risk ≠ certainty of developing disease
Disease risk may also depend on:
- environment
- lifestyle
- age
- other genes
- chance
For many common diseases, genetics is only one part of a much larger picture.
Monogenic and Complex Diseases
Some diseases are strongly associated with variants in a single gene.
These are sometimes called monogenic disorders.
Other diseases are much more complex.
Conditions such as many forms of:
- cardiovascular disease
- diabetes
- cancer
- autoimmune disease
can involve many genetic and environmental factors.
For complex diseases:
many genes + environment + lifestyle + age → overall risk
This makes prediction much more difficult.
Personalized Medicine Is Not Genetic Destiny
Suppose genetic testing shows that a person has an increased risk of Disease X.
This does not necessarily mean:
"You will develop Disease X."
It means the available evidence suggests their probability may differ from that of an appropriate comparison population.
Genetic information should therefore be interpreted as part of a larger medical picture.
Family Information
Because DNA is inherited, genetic testing can sometimes reveal information relevant not only to the patient but also to biological relatives.
For example, identifying an inherited disease-associated variant may indicate that:
- parents
- siblings
- children
could also carry the variant.
This creates unusual ethical questions because one person's medical test can potentially provide information about other people.
Genetic Counselling
Genetic counsellors and other appropriately trained healthcare professionals can help people understand genetic information.
They may help explain:
- why testing is being considered
- what results could mean
- limitations of testing
- inheritance patterns
- possible implications for relatives
- options after receiving results
This can be especially important when genetic results are uncertain or emotionally significant.
Personalized Prevention
Personalized medicine is not only about choosing drugs.
Information about individual risk can sometimes guide:
- screening
- monitoring
- preventive treatment
- lifestyle recommendations
For example, someone with a well-established inherited risk of a particular disease may be offered different screening strategies from someone at average risk.
The goal is to match healthcare more closely to the person's evidence-based risk profile.
Monitoring Treatment
Personalization does not end when treatment begins.
Doctors can monitor:
- symptoms
- blood tests
- imaging
- biomarkers
- drug concentrations
- side effects
Treatment can then be adjusted.
A useful model is:
select → treat → measure → adjust
rather than:
select → treat → never reconsider
Benefits of Personalized Medicine
More Appropriate Treatments
Biological information may help identify treatments more likely to work.
Fewer Ineffective Treatments
Patients may avoid some treatments unlikely to benefit them.
Improved Safety
Genetic or molecular testing may identify increased risk of particular adverse effects.
Better Dosing
Some tests can help guide drug selection or dosage.
Earlier Intervention
Risk information may support earlier screening or prevention.
Better Disease Classification
Diseases that appear similar may be divided into biologically meaningful subgroups.
Limitations of Personalized Medicine
Personalized medicine also has important limitations.
Genetic Information Is Incomplete
Scientists do not understand the significance of every genetic variant.
Biology Is Complex
Genes interact with:
- other genes
- environment
- age
- lifestyle
Tests Can Produce Uncertain Results
A VUS may provide no immediate clinical answer.
Cost
Sequencing, interpretation, specialist care, and targeted medicines can be expensive.
Access
Advanced testing may not be equally available.
Privacy
Genetic data can contain highly personal information.
Results Can Change
A variant considered uncertain today may be reclassified as scientific knowledge improves.
Genetic Privacy
DNA information is unusually sensitive.
A genome contains information that can potentially reveal:
- biological relationships
- inherited variants
- disease susceptibility
- ancestry
Important questions include:
- Who owns genetic data?
- Who can access it?
- How long should it be stored?
- Can it be shared for research?
- How should it be protected?
- What happens if a database is breached?
Data protection is therefore a major issue in genomic medicine.
Incidental Findings
Imagine a patient undergoes genome sequencing to investigate one condition.
Scientists unexpectedly discover a variant associated with another potentially serious condition.
This is an incidental or secondary finding.
Questions arise:
- Should the patient be told?
- What if the risk is uncertain?
- What if no treatment exists?
- What if the information affects relatives?
- What if the patient did not want to know?
Patients should therefore receive appropriate information about possible outcomes before broad genetic testing.
The Right Not to Know
More information is not always automatically beneficial.
Some people may choose not to learn certain genetic risks, especially when:
- disease cannot be prevented
- no effective treatment exists
- predictions are uncertain
This creates the concept of a right not to know certain genetic information.
Healthcare systems must balance:
- patient autonomy
- potential medical benefit
- family implications
- professional responsibilities
Bias in Genetic Databases
Genetic interpretation depends heavily on reference databases and research studies.
If some populations are underrepresented in genomic research, interpretation may be less accurate for those groups.
A variant that appears unusual in one database may actually be common in a population that has not been well represented.
This creates an important scientific and equity challenge:
Personalized medicine works best when the underlying research represents diverse populations.
Artificial Intelligence and Genomic Data
Modern genomic datasets can be enormous.
Computational systems and artificial intelligence can help researchers:
- identify patterns
- classify variants
- analyze medical images
- integrate different types of patient data
- identify possible treatment relationships
However, algorithms are only as reliable as:
- their training data
- their design
- their validation
- the context in which they are used
AI therefore does not eliminate the need for scientific evidence and clinical judgement.
From "One Size Fits All" to Precision Medicine
Traditional medicine is sometimes described too simply as:
one treatment for everyone
In reality, medicine has always considered individual differences such as:
- age
- body size
- allergies
- symptoms
- kidney function
- pregnancy
- other medications
Personalized medicine extends this idea by adding increasingly detailed molecular information.
A better comparison is:
traditional clinical information
genetic and molecular information
environmental and lifestyle information
=
more informed healthcare decisions
Worked Example 1: Pharmacogenomics
Two patients receive the same medicine.
Patient A metabolizes it rapidly.
Patient B metabolizes it slowly because of a genetic difference affecting a drug-metabolizing enzyme.
Why might the same dose produce different effects?
Answer
Patient B may break down the medicine more slowly.
The drug could remain at a higher concentration for longer.
This could change:
- effectiveness
- duration of action
- risk of side effects
Genetic information may therefore help guide dosing or drug choice in some situations.
Worked Example 2: Cancer Treatment
Two patients have the same general type of cancer.
Genetic analysis shows:
Patient A: tumour contains Mutation X
Patient B: tumour does not contain Mutation X
A drug specifically targets the protein activated by Mutation X.
Which patient is biologically more likely to be considered for this targeted treatment?
Answer
Patient A, because their tumour contains the molecular target the drug is designed to affect.
However, treatment decisions would still depend on additional clinical evidence and circumstances.
Worked Example 3: Genetic Risk
A genetic test shows that a person has a variant associated with increased risk of Disease Y.
The person says:
"That means I will definitely get Disease Y."
Is this necessarily correct?
Answer
No.
Risk is not the same as certainty.
Development of the disease may depend on:
- other genes
- environmental factors
- lifestyle
- age
- chance
The meaning of the result depends on the specific variant and scientific evidence.
Worked Example 4: Uncertain Variant
A patient receives this result:
Gene Z: Variant Q — uncertain significance
Should doctors automatically treat Variant Q as disease-causing?
Answer
No.
There is currently insufficient evidence to classify the variant confidently as harmful or harmless.
Medical decisions should not simply assume that an uncertain variant causes disease.
Worked Example 5: Evaluating Personalized Medicine
A new genetic test costs $2,000.
It predicts which of two treatments is more likely to work, but only for about 20% of patients.
Should every patient automatically receive the test?
Answer
More information is needed.
Healthcare systems would consider:
- strength of the evidence
- cost
- accuracy
- clinical benefit
- treatment costs
- alternatives
- risks
- accessibility
A technology can be scientifically useful without necessarily being appropriate for every patient.
Common Mistakes
Mistake 1: "Personalized medicine means making a completely unique drug for every patient."
Usually not.
It often means selecting or adjusting existing treatments based on relevant patient characteristics.
Mistake 2: "Personalized medicine only uses DNA."
Genetics is important, but personalized medicine can also use clinical, environmental, lifestyle, imaging, and biochemical information.
Mistake 3: "A genetic variant means something is wrong."
Everyone carries many genetic variants.
Most do not cause disease.
Mistake 4: "If a disease-associated gene is present, the person will definitely develop the disease."
Many genetic variants alter risk, not certainty.
Mistake 5: "Tumour mutations are always inherited."
Many tumour mutations are somatic, meaning they developed in cancer cells during the person's lifetime.
Mistake 6: "Sequencing DNA automatically tells doctors what treatment to use."
Sequencing produces data.
The data must still be interpreted using scientific and clinical evidence.
Mistake 7: "More genetic information is always better."
More data can also produce:
- uncertain findings
- incidental findings
- privacy concerns
- interpretation challenges
Mistake 8: "Whole-genome sequencing gives perfectly certain predictions."
Our understanding of the genome remains incomplete.
Many variants have uncertain or very small effects.
Mistake 9: "Genetic testing replaces doctors."
Genetic testing provides additional information that can support healthcare decisions.
It does not replace clinical judgement.
Mistake 10: "Personalized medicine guarantees successful treatment."
It can improve treatment selection in some circumstances, but biology remains complex and treatment outcomes cannot always be predicted.
Check Your Understanding
1. Personalized Medicine
Define personalized medicine in your own words.
2. Genetic Variation
Explain how two people can respond differently to the same medicine because of genetic variation.
3. DNA Analysis
Put these stages in a logical order:
- variants interpreted
- DNA extracted
- treatment options considered
- sample collected
- DNA analyzed
- relevant variants identified
4. Pharmacogenomics
Explain what pharmacogenomics studies.
Give one way pharmacogenomic information could influence treatment.
5. Cancer
Explain why two patients with cancers in the same organ might receive different treatments.
6. Germline vs Somatic
Explain the difference between:
germline genetic variants
and
somatic genetic variants.
7. Uncertainty
What is a variant of uncertain significance?
Why can such a result be challenging for patients and doctors?
8. Benefits
Identify four potential benefits of personalized medicine.
9. Challenges
Identify four challenges associated with personalized medicine.
10. Challenge
A patient's genome is sequenced to investigate a genetic disorder.
The analysis identifies:
- one likely disease-causing variant
- two variants of uncertain significance
- a separate variant associated with increased risk of another disease
- information that may also be relevant to the patient's siblings
Evaluate the challenges involved in communicating and using these results.
Consider:
- certainty
- clinical usefulness
- privacy
- family implications
- informed consent
- right not to know
- genetic counselling
Key Terms
- Personalized medicine – healthcare approach using individual biological and other relevant characteristics to guide medical decisions
- Precision medicine – approach that uses biological and other differences to improve prevention, diagnosis, or treatment
- Genetic variant – difference in a DNA sequence
- SNV – variation involving a single nucleotide
- SNP – common single-nucleotide variation within a population
- DNA sequencing – determining the order of nucleotides in DNA
- Gene panel – test examining a selected group of genes
- Exome – protein-coding regions of the genome
- Whole-exome sequencing (WES) – analysis of much of the protein-coding portion of the genome
- Whole-genome sequencing (WGS) – analysis of most of an individual's genome
- Variant of uncertain significance (VUS) – genetic variant whose relationship with disease is not sufficiently established
- Pharmacogenomics – study of how genetic variation affects responses to medicines
- Biomarker – measurable biological characteristic providing information about health, disease, or treatment response
- Targeted therapy – treatment designed to affect a particular biological molecule or pathway
- Molecular profiling – analysis of molecular characteristics of a disease such as cancer
- Germline variant – inherited or potentially inheritable genetic variant generally present throughout the body
- Somatic variant – genetic change acquired in particular cells during life
- Genetic counselling – professional support for understanding genetic information and its implications
- Incidental finding – medically relevant information discovered outside the original purpose of testing
- Genetic privacy – protection of information contained in genetic data
- Genomic medicine – use of genomic information in healthcare
Key Takeaways
- Personalized medicine uses individual biological and other relevant information to help guide healthcare decisions.
- Genetics is important, but personalized medicine also considers clinical, environmental, lifestyle, and biochemical information.
- Genetic variation can influence disease risk, drug metabolism, treatment effectiveness, and adverse reactions.
- DNA analysis and sequencing allow scientists to identify genetic variants that may have medical significance.
- Tests can range from examining one gene to gene panels, whole-exome sequencing, and whole-genome sequencing.
- Finding a genetic variant does not automatically mean that the variant causes disease.
- A variant of uncertain significance is a variant whose medical importance is not yet clear.
- Pharmacogenomics investigates how genetic differences influence responses to medicines.
- Genetic information can sometimes help doctors choose a medicine, adjust a dose, or avoid particular treatments.
- Cancer treatment increasingly uses molecular profiling to identify characteristics of tumours that may respond to targeted therapies.
- Tumour mutations can be somatic and are not necessarily inherited.
- Genetic risk is usually a probability, not a prediction of certainty.
- Personalized medicine can potentially improve treatment effectiveness, reduce some adverse reactions, improve disease classification, and guide prevention.
- Major challenges include cost, access, uncertain results, biological complexity, privacy, data security, and unequal representation in genetic databases.
- Genetic testing can reveal information relevant to biological relatives, creating additional privacy and ethical questions.
- More genetic data does not automatically mean better healthcare; information must be scientifically interpreted and clinically useful.
- Personalized medicine represents a shift toward combining genetics, biotechnology, data science, and traditional clinical information to make healthcare decisions more precisely suited to the patient.