3104NSC Drug Design and Delivery
The Complete Study & Assessment Guide · T2 20263104NSC Overview
- Griffith University School of Environment and Science
- Trimester 2, 2026
- an upper-level undergraduate science course
- 10 credit points
- a pharmaceutical and biomedical science course
3104NSC Drug Design and Delivery connects target discovery, molecular design, computational evidence, pharmacokinetics and delivery systems across the pharmaceutical development pathway. It is taught within Griffith University School of Environment and Science. It is an upper-level undergraduate science course.
- 3104NSC grading Quiz 1 20% · Quiz 2 20% · Drug-Target Interaction Assignment 10% · 2 more published item(s)
- 3104NSC task mode Plan around this operating format: No central final examination appears in the current 3104NSC assessment table.
- 3104NSC pressure point The main transfer challenge is this: Maintaining the causal chain from biological target to candidate properties, exposure and delivery.
- 3104NSC rule check Before relying on the total mark, apply this control: Treat the 3104NSC hurdle status as unconfirmed. Check the current course profile for any component-level pass rule before relying on the overall mark.
How 3104NSC is assessed
| Component | Weight | Format |
|---|---|---|
| Quiz 1 | 20% | Week 4; assesses discovery and early design material |
| Quiz 2 | 20% | Week 7; assesses the next course arc |
| Drug-Target Interaction Assignment | 10% | Week 10; applied written analysis |
| Quiz 3 | 20% | Week 11; later design and delivery material |
| Student Seminar Presentation | 30% | Week 12; scientific presentation linked to the learning outcomes |
The current table publishes three 20% quizzes, a 10% drug-target assignment and a 30% seminar presentation. It contains no final-examination row and does not state a component hurdle.
Current 3104NSC dates
| Date | Item | Control |
|---|---|---|
| 31 Aug 2026 | Quiz 2 | 20% task in the captured T2 teaching schedule |
| 7 Sep 2026 | Drug-Target Interaction Assignment | 10% task shown in the teaching schedule |
| 28 Sep 2026 | Quiz 3 | 20% task in the captured T2 teaching schedule |
| 5 Oct 2026 | Student Seminar Presentations | 30% final weighted task |
Dates are as published in the current course materials. Confirm exact deadlines and submission settings in the live LMS.
What 3104NSC covers
The sequence opens at Target-to-Patient Evidence Across Drug Design and Delivery, develops its central analytical shift in Bioinformatics, Data Mining and AI Evidence, and closes with Scientific Seminar and Integrated Candidate Argument.
Target-to-Patient Evidence Across Drug Design and Delivery
20/20/10/20/30 architecture · discovery-to-delivery chain · evidence-level control · map every assessment to the section of the development chain and the evidence level it can supportDefine 20/20/10/20/30 architecture
Target-to-Patient Evidence Across Drug Design and Delivery places 20/20/10/20/30 architecture, discovery-to-delivery chain and evidence-level control on a target-to-patient evidence chain.
- 20/20/10/20/30 architecture
- discovery-to-delivery chain
- evidence-level control
- Applying 20/20/10/20/30 architecture
- Limits of discovery-to-delivery chain and evidence-level control
Therapeutic Need, Target Discovery and Validation
therapeutic need · target discovery · target validation · compare genetic, biochemical and disease-model evidence before prioritising a targetDefine therapeutic need
Therapeutic Need, Target Discovery and Validation places therapeutic need, target discovery and target validation on a target-to-patient evidence chain.
- therapeutic need
- target discovery
- target validation
- Applying therapeutic need
- Limits of target discovery and target validation
Screening, Hits and Lead Selection
phenotypic screening · target-based screening · hit-to-lead optimisation · choose a screening strategy and define the evidence needed to move from hit to leadDefine phenotypic screening
Screening, Hits and Lead Selection places phenotypic screening, target-based screening and hit-to-lead optimisation on a target-to-patient evidence chain.
- phenotypic screening
- target-based screening
- hit-to-lead optimisation
- Applying phenotypic screening
- Limits of target-based screening and hit-to-lead optimisation
Structure-Based and Fragment-Based Drug Design
structure-based drug design · binding pocket · fragment-based drug design · interpret a binding pose and propose one change while preserving geometry and physicochemical constraintsDefine structure-based drug design
Structure-Based and Fragment-Based Drug Design places structure-based drug design, binding pocket and fragment-based drug design on a target-to-patient evidence chain.
- structure-based drug design
- binding pocket
- fragment-based drug design
- Applying structure-based drug design
- Limits of binding pocket and fragment-based drug design
Ligand Binding, Affinity and Selectivity
binding affinity · selectivity · structure-activity relationship · compare candidate modifications by affinity, selectivity and the mechanistic evidence behind a structure-activity trendDefine binding affinity
Ligand Binding, Affinity and Selectivity places binding affinity, selectivity and structure-activity relationship on a target-to-patient evidence chain.
- binding affinity
- selectivity
- structure-activity relationship
- Applying binding affinity
- Limits of selectivity and structure-activity relationship
Natural Products and Medicinal Scaffolds
natural product · molecular scaffold · dereplication · evaluate a natural-product hit as a source of mechanism, scaffold and supply constraintsDefine natural product
Natural Products and Medicinal Scaffolds places natural product, molecular scaffold and dereplication on a target-to-patient evidence chain.
- natural product
- molecular scaffold
- dereplication
- Applying natural product
- Limits of molecular scaffold and dereplication
Bioinformatics, Data Mining and AI Evidence
bioinformatics · virtual screening · predictive model validation · use computational ranking to prioritise experiments and state the validation required before biological interpretationDefine bioinformatics
Bioinformatics, Data Mining and AI Evidence places bioinformatics, virtual screening and predictive model validation on a target-to-patient evidence chain.
- bioinformatics
- virtual screening
- predictive model validation
- Applying bioinformatics
- Limits of virtual screening and predictive model validation
ADME, Pharmacokinetics and Pharmacodynamics
ADME · pharmacokinetics · pharmacodynamics · trace how one change in clearance or bioavailability alters exposure and expected effectDefine ADME
ADME, Pharmacokinetics and Pharmacodynamics places ADME, pharmacokinetics and pharmacodynamics on a target-to-patient evidence chain.
- ADME
- pharmacokinetics
- pharmacodynamics
- Applying ADME
- Limits of pharmacokinetics and pharmacodynamics
Routes, Formulation and Release
route of administration · dosage form · controlled release · select a route and dosage form from target site, stability, onset, adherence and manufacturing needsDefine route of administration
Routes, Formulation and Release places route of administration, dosage form and controlled release on a target-to-patient evidence chain.
- route of administration
- dosage form
- controlled release
- Applying route of administration
- Limits of dosage form and controlled release
Nanocarriers, Biomaterials and Targeted Delivery
nanocarrier · biomaterial · targeted delivery · compare carrier designs by loading, stability, release, targeting evidence, toxicity and manufacturabilityDefine nanocarrier
Nanocarriers, Biomaterials and Targeted Delivery places nanocarrier, biomaterial and targeted delivery on a target-to-patient evidence chain.
- nanocarrier
- biomaterial
- targeted delivery
- Applying nanocarrier
- Limits of biomaterial and targeted delivery
Safety, Translation and Development Risk
therapeutic index · off-target effect · translational validity · build a risk table linking mechanism, exposure, off-targets and model limitations to the next experimentDefine therapeutic index
Safety, Translation and Development Risk places therapeutic index, off-target effect and translational validity on a target-to-patient evidence chain.
- therapeutic index
- off-target effect
- translational validity
- Applying therapeutic index
- Limits of off-target effect and translational validity
Scientific Seminar and Integrated Candidate Argument
scientific seminar · candidate evidence dossier · claim-evidence-limit chain · present one candidate decision from therapeutic need through delivery while defending the weakest evidence linkDefine scientific seminar
Scientific Seminar and Integrated Candidate Argument places scientific seminar, candidate evidence dossier and claim-evidence-limit chain on a target-to-patient evidence chain.
- scientific seminar
- candidate evidence dossier
- claim-evidence-limit chain
- Applying scientific seminar
- Limits of candidate evidence dossier and claim-evidence-limit chain
It carries 10 credit points. It is positioned as a pharmaceutical and biomedical science course.
The learning journey moves from how a drug target is chosen to how a candidate is optimised and delivered.
Three quizzes distribute retrieval across the trimester, while the assignment and seminar require students to explain drug-target evidence and communicate a current design or delivery problem.
Assessment in 3104NSC is distributed as follows: Quiz 1 20%, Quiz 2 20%, drug-target interaction assignment 10%, Quiz 3 20%, and student seminar presentation 30%
The operational assessment conditions matter here.
No central final examination appears in the current 3104NSC assessment table. The final weighted task is the 30% student seminar presentation in Week 12.
What makes 3104NSC demanding is concrete: Maintaining the causal chain from biological target to candidate properties, exposure and delivery.
A plausible molecule is not enough: students must connect binding evidence, selectivity, physicochemical behaviour, metabolism, route and formulation to the therapeutic question without treating in-silico predictions as clinical proof.
Treat the 3104NSC hurdle status as unconfirmed.
Check the current course profile for any component-level pass rule before relying on the overall mark.
The sequence opens at Target-to-Patient Evidence Across Drug Design and Delivery, develops its central analytical shift in Bioinformatics, Data Mining and AI Evidence, and closes with Scientific Seminar and Integrated Candidate Argument.
Coverage note: contradictory Home-page link titles are not used to assign the Module 2 and Module 4 labels.
Worked example · free
Connect target potency to exposure and delivery
- 1Separate target-binding evidence from whole-body exposure evidence.
- 1Identify the ADME process most likely to reduce concentration over time.
- 1Propose one formulation, route or molecular-design response.
- 1State the next measurement needed before a progression decision.
Key terms
- Structure based drug design
- A design approach that uses three-dimensional target structure and molecular interactions to propose, rank and optimise candidate ligands.
- Drug target
- A biological molecule or process whose modulation by a therapeutic agent is expected to change a disease-relevant outcome.
- Target validation
- The accumulation of evidence that altering a proposed target produces the intended biological effect with acceptable specificity and relevance.
- Ligand binding
- The reversible association of a molecule with a biological target through shape, charge and intermolecular forces that determine affinity and selectivity.
- ADME
- The linked processes of absorption, distribution, metabolism and excretion that determine a drug's exposure over time in the body.
- Pharmacokinetics
- The quantitative study of drug concentration over time as absorption, distribution, metabolism and excretion alter systemic exposure.
- Drug delivery system
- A formulation, device or carrier designed to transport a therapeutic agent to the intended site at a controlled rate and dose.
- Bioinformatics
- The computational analysis of biological sequence, structure and functional data to generate and test hypotheses about targets and candidates.
- Fragment-based drug design
- A discovery strategy that screens small molecular fragments, then grows, links or merges validated binders into higher-affinity candidates.
3104NSC FAQ
How is 3104NSC assessed?
Quiz 1 20%, Quiz 2 20%, drug-target interaction assignment 10%, Quiz 3 20%, and student seminar presentation 30%
Which current 3104NSC dates are captured?
Quiz 2: 31 Aug 2026; Drug-Target Interaction Assignment: 7 Sep 2026; Quiz 3: 28 Sep 2026; Student Seminar Presentations: 5 Oct 2026. Confirm any change and the exact submission setting in the live LMS.
Where do students usually lose marks in 3104NSC?
Maintaining the causal chain from biological target to candidate properties, exposure and delivery. A plausible molecule is not enough: students must connect binding evidence, selectivity, physicochemical behaviour, metabolism, route and formulation to the therapeutic question without treating in-silico predictions as clinical proof.
What is the 3104NSC final assessed-task format?
No central final examination appears in the current 3104NSC assessment table. The final weighted task is the 30% student seminar presentation in Week 12.
Does 3104NSC have a hurdle or component-level pass rule?
Treat the 3104NSC hurdle status as unconfirmed. Check the current course profile for any component-level pass rule before relying on the overall mark.
What prerequisites or restrictions apply to 3104NSC?
Check the current official handbook before enrolling in 3104NSC; prerequisites are not inferred from its course number.
How does pharmacokinetics and pharmacodynamics appear in 3104NSC?
Pharmacokinetics describes what the body does to a drug through absorption, distribution, metabolism and excretion; pharmacodynamics describes what the drug does to its target and biological system. 3104NSC links both to candidate selection and delivery design.
Is this 3104NSC resource an official university guide?
No. It is an independent 3104NSC study resource; current institutional instructions remain authoritative for assessment operation.
Questions students ask in each 3104NSC chapter
- What is the main task in Target-to-Patient Evidence Across Drug Design and Delivery?
- Map every assessment to the section of the development chain and the evidence level it can support. Chapter 01 · Target-to-Patient Evidence Across Drug Design and Delivery
- What is the main task in Therapeutic Need, Target Discovery and Validation?
- Compare genetic, biochemical and disease-model evidence before prioritising a target. Chapter 02 · Therapeutic Need, Target Discovery and Validation
- What is the main task in Screening, Hits and Lead Selection?
- Choose a screening strategy and define the evidence needed to move from hit to lead. Chapter 03 · Screening, Hits and Lead Selection
- What is the main task in Structure-Based and Fragment-Based Drug Design?
- Interpret a binding pose and propose one change while preserving geometry and physicochemical constraints. Chapter 04 · Structure-Based and Fragment-Based Drug Design
- What is the main task in Ligand Binding, Affinity and Selectivity?
- Compare candidate modifications by affinity, selectivity and the mechanistic evidence behind a structure-activity trend. Chapter 05 · Ligand Binding, Affinity and Selectivity
- What is the main task in Natural Products and Medicinal Scaffolds?
- Evaluate a natural-product hit as a source of mechanism, scaffold and supply constraints. Chapter 06 · Natural Products and Medicinal Scaffolds
- What is the main task in Bioinformatics, Data Mining and AI Evidence?
- Use computational ranking to prioritise experiments and state the validation required before biological interpretation. Chapter 07 · Bioinformatics, Data Mining and AI Evidence
- What is the main task in ADME, Pharmacokinetics and Pharmacodynamics?
- Trace how one change in clearance or bioavailability alters exposure and expected effect. Chapter 08 · ADME, Pharmacokinetics and Pharmacodynamics
- What is the main task in Routes, Formulation and Release?
- Select a route and dosage form from target site, stability, onset, adherence and manufacturing needs. Chapter 09 · Routes, Formulation and Release
- What is the main task in Nanocarriers, Biomaterials and Targeted Delivery?
- Compare carrier designs by loading, stability, release, targeting evidence, toxicity and manufacturability. Chapter 10 · Nanocarriers, Biomaterials and Targeted Delivery
- What is the main task in Safety, Translation and Development Risk?
- Build a risk table linking mechanism, exposure, off-targets and model limitations to the next experiment. Chapter 11 · Safety, Translation and Development Risk
- What is the main task in Scientific Seminar and Integrated Candidate Argument?
- Present one candidate decision from therapeutic need through delivery while defending the weakest evidence link. Chapter 12 · Scientific Seminar and Integrated Candidate Argument
How to prepare for the assessments
Retrieve the course map, practise the recurring method—connect the therapeutic problem to a validated target, candidate interaction, exposure profile and delivery design, then qualify the evidence at the laboratory, organism and clinical levels—on changed scenarios, and verify every operational assessment detail in the live institutional system.
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