1-1,2 - Intro Flashcards

1
Q

Describe a basic dose-response curve (X and Y axis?, what do different parts mean?)

A

X axis = concentration of drug
Y axis = % relative to maximum response
Where slope flattens out at top is where maximum effect is. Where Y value is just above 0 is minimum/threshold dose.

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2
Q

3 factors that describe a drug on the dose-response curve?

A
  • Affinity – Binding of drug to target site and how well it does this.
  • Potency – Required concentration to reach 50% of maximum efficacy
    Note: High affinity -> high potency
  • Efficacy – Maximum response of patient to drug at high enough concentrations.
    Note: Efficacy indepedent of affinity and potency
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3
Q

How do the 3 factors that describe a drug affect the dose-response curve?

A
  • The difference in affinity (and thereby potency) will show up as a shift along the X axis relative to other drugs. This is because a different concentration is required to reach 50% efficacy. The maximum response remains on the same Y level as efficacy is unchanged.
  • A decrease in efficacy will reduce the maximum value and so the flatten slope at the top is lower. The potency remains the same concentration assuming potency stays the same but the peak response differs.
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4
Q

Two measures for bioequivalence and how to measure for slopes of same efficacy but different potencies?

A

Bioequivalence measures relative effect between two drugs.
- M (potency ratio or equipotent dose) is concentration of standard divided by concentration of unknown at given % response. This is seen as measuring along the X axis e.g. if at 20% efficacy, standard drug requires 1.5 microliters whilst new drug only needs 0.5, then ratio is 3.
- A (difference in magnitude) is seens as measure along Y axis (at same conc.)

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5
Q

How do we measure the risk vs benefit of a drug?

A

Measure a population and their response to a drug.
On a graph of
X axis = increasing dose
Y axis = % of individuals responding,
Find
TD50 = toxic dose where 50% of population get side effects
and
ED50 = effective dose where 50% of population experience wanted effects.
The therapeutic index ratio (TI) is found as TD50/ED50 and describes relative effect of wanted and unwanted effects. This is the “saftey margin”.
Therapeutic window is dose range where minimal adverse effects occur whilst still being effective for most patients.

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6
Q

Difference between specificity and selectivity?

A
  • Specificity means specific location e.g. eye, heart, lungs, brain, liver.
  • Selectivity means specific target site e.g. a drug that only affects one type of receptor is selective.
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7
Q

Generally, increasing dose will increase/decrease specificity/selectivity

A

Decrease specificity

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8
Q

Describe how stereoisomers can affect either specificity or selectivity.

A

Stereoisomers have different shapes and thereby affect different target receptor sites. This affects selectivity.

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9
Q

1) What do bioassays measure?
2) Good features of a bioassay?

A

1) Pharmokinetics, pharmacodynamics, specificity, selectivity, basically how good a drug is.
2)
- reproducible (consistent response)
- Reliable
- Effectively compare with other drugs.

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10
Q

Names for different types of stages of clinical stages
1) Testing on petri dish
2) Testing tissue isolated from animal
3) Testing on live animal

A
  • In vitro = Test on cells in petri dish
  • Ex vivo = Test on tissue outside of the organism it came from e.g. eye from animal is isolated and put on petri dish.
  • In vivo = Done on living animal e.g. inject into mice.
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11
Q

Limitations of animal models?

A
  • Similar pathophysiological phenotype (face validity) (same symptoms)
  • Similar causation (construct validity)
  • Similar response to treatment (predictive validity)
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12
Q

Why do most clinical trials fail?

A
  • Clinical efficacy low
  • Poor drug properties
  • Lack of commercial interest
  • Poor strategic planning
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13
Q

Describe the different phases of clinical trials. For each phase,
- Purpose
- No. of participants
- Time-scale

A

Phase:
1 – Determine safety in healthy patients.
10 – 20 participants
Several months
2 – Pharmacokinetic + dynamic studies in patients and control alike. Assess initial efficacy
100s of patients
Months to years
3 – Phase 2 but assess long term effects.
1000s of patients
Several years
4 – Post-market surveillance to ensure future safety.
Several 1000s of patients
Long term.

Note that sample size will vary depending on drug.

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14
Q

What’s a biomarker?

A

An objective way of measuring the endpoint (success) of a drug.
Can be obj. or sbj. measure

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15
Q

Simple vs stratified randomisation?

A

Simple is picking random people into each group. Stratified is subdividing participants into smaller groups first before choosing groups. E.g. separate males from females, then over 50 from under 50. Then half from every group to be control and other half for treatment. This increase similarities in demographic.

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16
Q

How to calculate relative risks and odds ratios?

A

RR = Risk for patient in treatment/risk for patient in control
OR = Odds for patient in treatment/Odds for patient in control
Risk = Affected/total
Odds = Affected/Unaffected

17
Q

1) How to calculate RRR?
2) How to calculate NNT? What is NNT?
3) If drug A halfs death rate from 50% to 25% and drug b halves 5% to 2.5% death rate, which is larger NNT?

A

1) Relative Risk Reduction = 1 – RR
Then calculate ARR (Absolute Risk Reduction) which is Risk in group – risk in treatment.
In an example, 75% get heart attacks w/o Tx whilst 25% get heart attacks on Tx. RR = 0.25/0.75 = 0.33, 1 – RR = 1 – 0.33 = 0.66 (ppl 66% less likely to get heart attack if on Tx)

Calculate NNT using 1/ARR (where ARR is risk in control minus risk in Tx)
NNT = Number needed to treat (in order to measure efficacy)
In that same example, AAR = 0.75 - 0.25 = 0.5 (50% of ppl will stop getting heart attacks when on Tx), NNT = 1/ARR = 1/0.5 = 2

Drug B. Since the absolute risk is low, NNT is high. This means more people are needed to prove effectiveness.

18
Q

Type 1 vs type 2 errors

A
  • Type I = False positive, reject null hypothesis when it’s true. Very dangerous as you think treatment works when it actually doesn’t.
  • Type II = False negative, accept null hypothesis when it’s false.