Publications by authors named "U Klinkhardt"

Article Synopsis
  • Prime-2-CoV_Beta is a new COVID-19 vaccine candidate that uses an Orf virus to express the nucleocapsid and spike proteins from SARS-CoV-2, specifically the Beta strain.
  • In Phase I clinical trials, the vaccine was found to be safe and able to generate immune responses, but further studies were needed due to the evolving variants, particularly Omicron.
  • Research in mice and hamsters showed that while Prime-2-CoV_Beta elicited strong immune responses in unvaccinated animals, it did not significantly boost immunity in already immunized subjects and demonstrated similar protection levels between different immunization strategies.
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Background: Preclinical studies demonstrate synergism between cancer immunotherapy and local radiation, enhancing anti-tumor effects and promoting immune responses. BI1361849 (CV9202) is an active cancer immunotherapeutic comprising protamine-formulated, sequence-optimized mRNA encoding six non-small cell lung cancer (NSCLC)-associated antigens (NY-ESO-1, MAGE-C1, MAGE-C2, survivin, 5T4, and MUC-1), intended to induce targeted immune responses.

Methods: We describe a phase Ib clinical trial evaluating treatment with BI1361849 combined with local radiation in 26 stage IV NSCLC patients with partial response (PR)/stable disease (SD) after standard first-line therapy.

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Mathematical models of tumor dynamics generally omit information on individual target lesions (iTLs), and consider the most important variable to be the sum of tumor sizes (TS). However, differences in lesion dynamics might be predictive of tumor progression. To exploit this information, we have developed a novel and flexible approach for the non-parametric analysis of iTLs, which integrates knowledge from signal processing and machine learning.

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Mathematical models of tumor size (TS) dynamics and tumor growth inhibition (TGI) need to place more emphasis on resistance development, given its relevant implications for clinical outcomes. A deeper understanding of the underlying processes, and effective data integration at different complexity levels, can foster the incorporation of new mechanistic aspects into modeling approaches, improving anticancer drug effect prediction. As such, we propose a general framework for developing future semi-mechanistic TS/TGI models of drug resistance.

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Background: The OPUS study demonstrated that addition of cetuximab to 5-fluorouracil, folinic acid and oxaliplatin (FOLFOX4) significantly improved objective response and progression-free survival (PFS) in the first-line treatment of patients with KRAS exon 2 wild-type metastatic colorectal cancer (mCRC). In patients with KRAS exon 2 mutations, a detrimental effect was seen upon addition of cetuximab to FOLFOX4. The current study reports outcomes in subgroups defined by extended RAS testing.

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