Patent: 10,308,985

Summary for Patent: 10,308,985

Title:	Methods for diagnosing risk of renal allograft fibrosis and rejection
Abstract:	Disclosed herein is a method for diagnosing a renal allograft recipient\'s risk for developing fibrosis of the allograft and allograft loss. The method includes determining the expression levels of certain microRNAs, which have been determined to be predictive of an allograft recipient\'s risk. Also disclosed herein is a method of treating a renal allograft recipient to inhibit fibrosis of the allograft and allograft loss, as well as kits for use in the methods disclosed herein.
Inventor(s):	Murphy; Barbara (Pelham Manor, NY), Zhang; Weijia (Cresskill, NJ)
Assignee:	Icahn School of Medicine at Mount Sinai (New York, NY)
Application Number:	15/320,208
Patent Claims:	see list of patent claims

United States Patent 10,308,985: Critical Claim Review and US Patent Landscape for miRNA-Based Renal Allograft Fibrosis Risk and Therapy

What does US 10,308,985 actually claim, in enforceable terms?

US Patent 10,308,985 claims a diagnostic-to-therapeutic method for renal allograft recipients using a specific microRNA panel measured by Nanostring, tied to a risk classification model and followed by administering an anti-fibrosis or anti-rejection drug (with multiple dependent claim variations on drug selection, risk cutoffs, and modeling method). The claims are structured so that broad “method of diagnosing and treating” coverage hangs on the combination of (i) the four-miRNA expression panel, (ii) Nanostring analysis (or Nanostring in core claim language), (iii) altered expression versus a control and/or a training-set-derived cutoff, and (iv) administering an effective drug.

Core claim architecture (Claim 1)

Claim 1 is the anchor:

• Sample: blood sample from a renal allograft recipient.
• Assay: Nanostring analysis of specific microRNAs:
  • hsa-miR-128
  • hsa-miR-29b-3p
  • hsa-miR-302b-3p
  • hsa-miR-192-5p
• Control: a control sample analyzed for each microRNA by Nanostring.
• Diagnosis trigger: recipient is “at risk” if expression levels are altered relative to control for each microRNA.
• Treatment linkage: treat by administering an effective amount of a drug for treating fibrosis of the allograft and allograft loss.
• Method framing: “diagnosing and treating … at risk for developing fibrosis … and allograft loss” using the panel and comparison.

Key dependent claim additions (Claims 2–19)

The dependent claims tighten specificity around (a) directionality and cutoff logic, (b) risk modeling with penalized logistic regression, (c) processing steps, (d) device chemistry, and (e) drug selection, including dose language and regimen modification.

Risk stratification logic

• Claim 2 adds “high risk” criteria based on directionality:

  • hsa-miR-128 and hsa-miR-302b-3p increased vs control
  • hsa-miR-29b-3p and hsa-miR-192-5p decreased vs control
  • based on a probability score cutoff determined from the training set.

• Claim 15 adds “low risk” criteria based on opposite directionality:

  • hsa-miR-128 and hsa-miR-302b-3p decreased vs control
  • hsa-miR-29b-3p and hsa-miR-192-5p increased vs control
  • also tied to a probability score cutoff from a training set.

Modeling method

• Claim 4: risk calculation uses penalized logistic regression.
• Claim 5 and Claim 19: risk probability computed using an equation defining p(x) as probability of developing fibrosis, with penalized coefficients (β) and gᵢ as expression value of each miRNA.
• Claim 5 and Claim 19 include formula placeholders consistent with a penalized logit score-to-probability mapping, but the claim text provided in the prompt renders the equation with formatting fragments.

Assay workflow

• Claim 3: includes “isolating mRNA,” “synthesizing cDNA from the mRNA,” then measuring microRNAs. This is notable because microRNAs are not typically measured as mRNA; the claim language may reflect the patent’s specific library-prep and detection approach, but it creates a potential internal-terminology ambiguity for claim construction and novelty arguments.
• Claim 10: expression can be determined by assay selected from qPCR, microarray, and Nanostring analysis. This widens “assay method” coverage beyond Nanostring, even though Claim 1 itself recites Nanostring analysis.
• Claim 11: adds a Nanostring procedural detail: annealing cDNA to barcode probes, immobilizing, and quantifying bound probes by a digital analyzer.

Drug scope The claims do not limit to one fibrosis therapy; instead they define multiple drug “buckets” for dependent claims:

• Anti-rejection drugs:

  • Claim 6: cyclosporine and Belatacept
  • Claim 13: modifying regimen with Belatacept, rapamycin, Mycophenolate Mofetil
  • Claim 18: anti-rejection drug is rapamycin
  • Claim 7 adds a dosing range for cyclosporine: 4–6 mg/kg bodyweight/day

• Immunosuppressive or anti-proliferative agents:

  • Claim 8: “immunosuppressive or anti-proliferative agent”
  • Claim 9: members include MMF, sirolimus, prednisone, Mycophenolate Sodium, Azathioprine (and also repeats MMF variant naming)

• Anti-fibrosis agents:

  • Claim 14: Pirfenidone, relaxin, BMP-7, HGF 6
  • Claim 17: same list for anti-fibrotic agent selection.

Regimen modification

• Claim 12: modifying immunosuppression regimen for recipients diagnosed high risk.
• Claim 16: administering anti-fibrotic agent for recipients diagnosed low risk.

Claim breadth and likely enforceability choke points

This family of claims is strong where competitors must do all of the following:

1. Measure the same four miRNAs in blood.
2. Use a Nanostring-based workflow (at least in Claim 1 and Claim 11).
3. Apply a control-relative altered expression decision, and in dependent claims, a directionality + training cutoff logic.
4. Tie diagnosis to a treatment regimen with fibrosis and allograft loss interventions (dependent claims add specific drug lists).

Potential choke points that could narrow enforcement in practice:

• If competitors use a different assay platform or different normalization/processing that changes what counts as “Nanostring analysis” or the claimed workflow in Claim 11.
• If competitors avoid the four-miRNA panel, or replace it with an expanded panel or different biomarker set.
• If competitors use a different statistical model (for the dependent claims on penalized logistic regression) rather than “penalized logistic regression” with coefficients and the claimed equation structure.
• If competitors treat using anti-rejection drugs only, without the claimed “drug for treating fibrosis of the allograft and allograft loss” linkage (or vice versa depending on which dependent claim they practice).

Why the drug and assay dependencies matter for freedom-to-operate

The enforceable “unit of infringement” in method claims is the complete method steps. Dependent claims add more specificity, which can cut both ways:

• They can narrow the scope, making it easier for a competitor to design around.
• They also provide multiple entry points if a product or clinical protocol aligns with at least one dependent claim path.

Drug selection creates multi-lane risk

A competitor running clinical care that includes:

• cyclosporine within 4–6 mg/kg/day for high-risk fibrosis stratification (Claim 7 + Claim 2 framework), or
• Belatacept/rapamycin/MMF regimen modifications triggered by risk (Claim 13/18), or
• anti-fibrotic agents such as pirfenidone (Claim 14/17) given based on low-risk diagnosis (Claim 16)

can trigger dependent claim exposure even if the broader diagnostic method is implemented with variations.

Assay step dependencies broaden “how” coverage

Even though Claim 1 is Nanostring, Claim 10 lists qPCR and microarray alternatives. That matters because many labs will not run Nanostring for routine monitoring, but could still practice the broader “assay selected from … qPCR, microarray, and Nanostring analysis” in a manner that still meets dependent claims.

Nanostring procedural steps are a partial technical lock

Claim 11’s annealing to barcode probes, immobilization, and quantifying bound probes via digital analyzer is consistent with standard Nanostring workflows. Any competitor using a different microRNA detection chemistry or instrument architecture may reduce direct compliance with Claim 11, though Claim 1 may still be practiced if Nanostring analysis occurs.

What is the likely US patent landscape posture around these claims?

A complete, citation-backed landscape requires identifying the relevant patent family members, priority dates, assignee/applicant, and the exact publication numbers associated with US 10,308,985, then mapping them to prior art and adjacent filings (miRNA biomarkers in transplant fibrosis; Nanostring miRNA panels; predictive modeling with logistic regression; and treatment selection triggers in renal allografts). The prompt provides only the claim set, not the bibliographic metadata or the patent’s publication/publication history.

Under the constraints here, a complete and accurate “comprehensive and critical analysis” with a US landscape map cannot be produced.

So the only defensible landscape analysis available from the supplied information is claim-logic positioning, not prior-art ranking or competitor identification.

Critical assessment: where the claims sit relative to common prior-art themes

Even without citing specific external patents, the claim set reveals the novelty strategy: it combines biomarker specificity (four miRNAs), sample type (blood), measurement modality (Nanostring; also allows other assay formats in dependent claim 10), decision logic (control-relative altered expression; training cutoff with directionality), statistical method (penalized logistic regression), and therapy linkage (anti-fibrosis vs anti-rejection with named agents).

Biomarker-panel specificity is the primary differentiation lever

Many transplant monitoring patents use:

• larger miRNA panels,
• tissue biopsies rather than blood,
• different miRNAs,
• different assay technologies (RT-qPCR, sequencing),
• and generic risk scores.

US 10,308,985 is pinned to the exact four miRNAs. If competitors use even one different miRNA, the dependent and independent claims keyed to the same set may not be met.

Modeling language may be both protective and fragile

“Penalized logistic regression” and a defined equation can increase differentiation from generic “risk score” assertions. But it also increases attack surface:

• A competitor could argue their model is not “penalized logistic regression.”
• They can potentially use a different regularization structure or model form (e.g., lasso/elastic net naming vs “penalized logistic regression” wording, or a non-linear model) to argue non-infringement for dependent claims 4/5/19.

Treatment linkage is broad but functionally constrained

Claim 1 says “administering an effective amount of a drug for treating fibrosis.” That is broad in drug category, but dependent claims carve out specific drugs. In enforcement, the key will be whether clinical use following diagnosis fits the defined “drug for treating fibrosis of the allograft and allograft loss” and whether regimen modification is triggered at the diagnosis thresholds.

Practical implications for R&D and investment diligence

If you are developing a competing diagnostic

High-risk exposure zones for competitors:

• same four-miRNA panel
• measured in blood
• delivered via Nanostring analysis
• risk classification using control comparison and optionally training-derived cutoff
• treatment decisions implemented on the basis of that risk

Design-around levers:

• replace or expand biomarker set so it no longer matches the four-miRNA claim set
• use an assay that avoids “Nanostring analysis” when the independent claim is targeted (or avoid a Nanostring-defined workflow where appropriate)
• use a different decision logic that does not rely on the described cutoff directionality framework (Claims 2 and 15)
• avoid penalized logistic regression for the risk score calculation in dependent claims (Claims 4/5/19)

If you are developing a therapeutic protocol

If a clinical protocol ties immunosuppression changes or anti-fibrotic drug administration to a miRNA-based diagnosis meeting the claim steps, it becomes a method-practice issue rather than a drug-only issue.

Drug-specific exposures:

• cyclosporine 4–6 mg/kg/day in this diagnostic-triggered setting (Claim 7)
• Belatacept and rapamycin regimen modifications in response to high-risk diagnosis (Claims 6, 13, 18)
• pirfenidone, relaxin, BMP-7, HGF 6 as anti-fibrotic agents linked to low-risk/high-risk logic (Claims 14/15/16/17)

Key Takeaways

• US 10,308,985 centers on a blood-based four-miRNA panel (hsa-miR-128, hsa-miR-29b-3p, hsa-miR-302b-3p, hsa-miR-192-5p) measured using Nanostring analysis, tied to control-relative altered expression and risk classification.
• Dependent claims add directionality and training-set cutoff logic (high vs low risk) plus a risk calculation using penalized logistic regression.
• Therapeutic exposure spans anti-rejection and anti-fibrotic strategies, including named agents and a specific cyclosporine dosing range (4–6 mg/kg/day).
• From a freedom-to-operate perspective, infringement risk concentrates around combinations that match: (i) the four miRNAs, (ii) the Nanostring-based measurement, (iii) the risk logic (including cutoff/directionality for dependent claims), and (iv) the diagnosis-triggered treatment linkage.

FAQs

1. Is Nanostring required for all claims in US 10,308,985?
   Independent Claim 1 recites Nanostring analysis, while dependent Claim 10 also lists qPCR and microarray options as alternative assay selections.

2. What determines “high risk” vs “low risk” in the dependent claims?
   Claims 2 and 15 set opposite directionality patterns for two miRNAs increased and two decreased, each tied to a training-set-derived probability score cutoff.

3. Does the patent require a specific statistical model?
   Claims 4/5/19 require penalized logistic regression for calculating risk probability in those dependent claim paths.

4. Which therapies are explicitly listed?
   Anti-rejection/immunosuppression examples include cyclosporine, Belatacept, rapamycin, MMF, sirolimus, prednisone, mycophenolate sodium, azathioprine; anti-fibrotic examples include pirfenidone, relaxin, BMP-7, HGF 6.

5. Where is the most concrete dosing specificity?
   Claim 7 specifies cyclosporine dosing as 4–6 mg/kg bodyweight/day.

References

No references can be produced from the provided prompt because no bibliographic identifiers (publication number, filing date, assignee) or external source data were provided.

Details for Patent 10,308,985

Applicant	Tradename	Biologic Ingredient	Dosage Form	BLA	Approval Date	Patent No.	Expiredate
Bristol-myers Squibb Company	NULOJIX	belatacept	For Injection	125288	June 15, 2011	10,308,985	2035-06-26