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Introduction: Lung cancer remains the leading cause of cancer-related deaths. Surgery is the best option for early lung cancer, and the role of adjuvant therapy remains controversial. Liquid biopsy offers a noninvasive approach to monitor cancer burden. Targeted sequencing of circulating cell free tumor DNA (ctDNA) in blood has shown success for diagnosis; however, low tumor burden and dynamic evolution of low stage disease is challenging for targeted panels. Thus, we hypothesized that a whole genome sequencing (WGS)-derived patient specific mutational signature from a matched tumor-normal WGS can provide sensitive and specific approach to detect mutations and copy numbers in ctDNA for monitoring of lung adenocarcinoma patients. Methods: We successfully profiled 50 Stage 1 or 2 lung adenocarcinomas. ctDNA was extracted from 1-2 mL of plasma, tumor DNA was extracted from pathology tissue and normal germline DNA from the white blood cells. WGS using was performed on matched tumor and normal DNA, and ctDNA extracted from plasma. WGS coverage was 40x for matched tumor-normal and 20x for ctDNA. We derived a personalized mutational pattern for each tumor and used an AI-based error suppression model for quantification and ultra-sensitive detection of ctDNA in plasma samples. A patient-specific personalized genome-wide compendium of somatic mutations and copy numbers was established and ctDNA tested at 3 to 18 available time points during the therapy or follow up. A personalized mutational signature for detection ctDNA from WGS was quantified and the ctDNA Tumor Fraction (TF) was compared to the clinical status and time to recurrence. Results: Tumor specific signatures were derived from matched tumor-normal samples with >5% tumor purity and Conclusions: Patient-specific WGS tumor signature from plasma derived ctDNA enables specific and ultrasensitive tracking of minimal residual disease in low stage lung adenocarcinoma patients. Molecularly positive status can be used to predict recurrence and identify patients with clinical low stage disease that may benefit from adjuvant therapy. Citation Format: Ivy Tran, Alejandro Vargas, Reid Wilkins, Isabella Pizzillo, Kenneth Tokoro, Danielle Afterman, Tomer Lauterman, Maja Kuzman, Santiago Gonzalez, Dunja Glavas, James Smadbeck, Dillon Maloney, Jurica Levatic, Samuel Phillips, Sunil Deochand, Michael Yahalom, Ryan Ptashkin, Iman Tavassoly, Zohar Donenhirsh, Eric White, Ravi Kandasamy, Ury Alon, Paz Polak, Boris Oklander, Asaf Zviran, Matija Snuderl, Harvey I. Pass. Whole genome cell-free tumor DNA mutational signatures from blood for early detection of recurrence of low stage lung adenocarcinoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6689.

Introduction: Liquid biopsy offers a noninvasive approach to monitor cancer burden during therapy and surveillance period. However, in pediatric brain cancers, liquid biopsy methods from the blood have been unsuccessful due to a low tumor burden and low number of mutations in coding regions. We hypothesized that a whole genome sequencing (WGS)-derived patient specific mutational signature from a matched tumor-normal WGS can provide a sensitive and specific approach to detect mutations in circulating cell free tumor DNA (ctDNA) and provide blood-based monitoring in pediatric patients with brain tumor. Methods: All tumors were analyzed and molecularly subclassified using whole genome DNA methylation profiling and machine learning classifier. Tumor DNA was extracted from pathology tissue and normal germline DNA from the white blood cells, while ctDNA was extracted from 1-2 mL of post-surgery or follow-up plasma samples, WGS was applied to sequence DNA from matched tumor-normal and plasma samples. WGS coverage was 40x for matched tumor-normal DNA and 20x for ctDNA. Using the C2i assay, we derived a personalized mutational pattern for each tumor and used an AI-based error suppression model for quantification and ultra-sensitive detection of ctDNA in plasma samples. A patient-specific personalized genome-wide compendium of somatic mutations was established and ctDNA tested at 1 to 3 available time points during the therapy or surveillance period. An AI-based error suppression model was implemented to filter out the noise in the cell free DNA (cfDNA) while the personalized mutational signature was used to detect the ctDNA in the cfDNA and to amplify the somatic signal contained in it. The ctDNA Tumor Fraction (TF) was compared to the clinical status and MR-based imaging. Results: We profiled 7 pediatric brain tumors, including 2 medulloblastomas (one Group 3, one Group 4), 3 pediatric glioblastomas IDH wild-type, 1 ependymoma PFA subtype and one low grade ganglioglioma. Tumor specific signatures were identified and detected in the plasma of 5 patients with clinical disease with a TF range 0.02-0.0005 but not in 2 patients with no tumor at the time of blood collection. In two children with a medulloblastoma and glioblastoma, the decrease of tumor fraction in ctDNA over 2 (TF: 0.002 to 0.0009) and 3 time points (TF: 0.0005 to undetectable), respectively, correlated with response to therapy based on imaging. Conclusions: Patient-specific WGS tumor signature in ctDNA from blood can be used for sensitive monitoring of children with brain tumors. Citation Format: Ivy Tran, Kristyn Galbraith, Guisheng Zhao, Robyn Borsuk, Joyce Varkey, Sharon Gardner, Jeffrey Allen, David Harter, Jeffrey Wisoff, Eveline T. Hidalgo, Sunil Deochand, Dillon Maloney, Danielle Afterman, Tomer Lauterman, Noah Friedman, Imane Bourzgui, Nidhi Ramaraj, Zohar Donenhirsh, Ronel Veksler, Jonathan Rosenfeld, Ravi Kandasamy, Iman Tavassoly, Boris Oklander, G. Praveen Raju, Theodore Nicolaides, Asaf Zviran, Matija Snuderl. Whole genome cell-free tumor DNA mutational signatures for noninvasive monitoring of pediatric brain cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3401.

Background: While detection of circulating tumor DNA (ctDNA) is associated with poor cancer prognosis, the clinical utility for guiding treatment decisions is unresolved. Patients with minimal residual disease (MRD) often have less than one genome equivalent of ctDNA per 10 mL blood. Consequently, it is stochastic whether a 10 mL sample contains ctDNA from a particular genomic locus. Consequently, the sensitivity of ctDNA detection methods targeting a limited number of tumor loci is heavily affected by sampling bias. To overcome this challenge, we developed MRDetect; a whole genome sequencing (WGS) approach, which detects ctDNA using the patient-specific cumulative signal from tens of thousands of mutations throughout the genome. Recently, we showed how MRDetect found ctDNA fractions down to 10-4. Here, we performed a validation study to confirm the prognostic impact of MRDetect. Aim: Validation of MRDetect for sensitive ctDNA detection to monitor residual disease in stage III colorectal cancer (CRC) patients treated with curative intent. Methods: From a large, uniform cohort of stage III CRC patients n = 146), we had plasma samples collected every third month (n = 938, median = 9 per patient) and a median follow-up of 34 months. For each patient, a genome-wide mutational signature was established by WGS of tumor and matched normal DNA. Enhanced by an AI-based error suppression model, this signature was used to detect ctDNA in 1-2 mL plasma samples using WGS (20x coverage). We used de-novo point mutation and copy number variation analysis to investigate cancer evolution after treatment. To evaluate the reproducibility of MRDetect, aliquot samples (n = 2x190 samples) from 5 recurrence and 10 non-recurrence patients were processed and sequenced at two independent laboratories. Outcome measures: ctDNA status, tumor fraction, false positive rate, Time To ctDNA Recurrence (TTcR), and Time To radiological Recurrence (TTrR). Results: Analysis of paired samples showed great reproducibility with high agreement between both ctDNA status calls (Cohens Kappa = 0.81) and the estimated tumor fractions (r2 = 0.99). MRDetect revealed post-operative ctDNA in all recurrence patients (5/5) with detected tumor fractions down to 2 x 10-4. Median TTcR was 0.9 month (range 0.5 - 7.3 months) while median TTrR was 12.8 months (range 11.3 - 31.1 months). The false positive rate was 1% (1/100), assessed in longitudinal samples from the 10 non-relapsing patients. Tumor evolution dynamics in plasma samples revealed novel amplification and deletions, which were absent in the primary tissue but confirmed in metachronous metastases. We will present results from the full cohort at AACR 2022. Conclusion: MRDetect detects ctDNA with high sensitivity and specificity and enables effective postoperative assessment of MRD, cancer evolution dynamics and early relapse detection. Citation Format: Amanda Frydendahl, Thomas Reinert, Jesper Nors, Sunil Deochand, Dillon Maloney, Noah Friedman, Tomer Lauterman, Danielle Afterman, Imane Bourzgui, Nidhi Ramaraj, Zohar Donenhirsh, Ronel Veksler, Ravi Kandasamy, Iman Tavassoly, Jonathan Rosenfeld, Anders Husted Andersen, Uffe S. Løve, Per V. Andersen, Ole Thorlacius-Ussing, Lene Hjerrild Iversen, Kåre Andersson Gotschalck, Boris Oklander, Asaf Zviran, Claus Lindbjerg Andersen. Sensitive detection of circulating tumor DNA by whole genome sequencing: Validation of MRDetect using serial blood samples from stage III colorectal cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1959.

Background: Early detection of recurrence and monitoring of MRD post-surgery is critical for clinical decision-making to tailor adjuvant therapy. In early-stage NSCLC, circulating tumor DNA (ctDNA) detection is especially challenging, requiring highly sensitive and specific assays. Therefore, we used a WGS approach (MRDetect) for ultra-sensitive ctDNA detection in NSCLC patients (pts) undergoing curative surgery. Methods: We conducted a pilot study to evaluate the MRDetect approach in serial plasma samples (including pre-surgery, post-surgery and follow-up [f/u] timepoints) from resected stage IB-IIIA NSCLC pts. Pts underwent routine surveillance by computed tomography scans. ctDNA was extracted from ~1mL plasma. MRDetect uses WGS by a tumor-informed approach (sequencing coverage 40x for tumor, 20x for plasma DNA) combined with AI-based error suppression models (trained and calibrated with a non-cancer cohort, n=17) to increase the signal to noise ratio for precise ctDNA detection, and improve the accuracy of readouts especially for low tumor burden scenarios. The assay reports the detection and quantification of ctDNA burden in blood with a prognostic value for risk of recurrence. The ability of the assay to predict recurrence from a single sample, taken at the clinical landmark point (median 1.6 mths post-surgery, range 0.1-6.5) was evaluated. Results: Overall, 52 NSCLC pts were enrolled (n=88 plasma samples) with median clinical f/u of 32.6 mths (range 3.1-98.6). There were 43 pts with post-surgery landmark samples, with median age 62 years, 70% were male, 79% were adenocarcinoma and 49% were EGFR mutated. 26% were stage IB and 37% each were stage II and III. There were 15/18 (sensitivity 83%) pts with confirmed radiological recurrence in which MRDetect was positive, including 6/7 (86%) EGFR mutated pts. The median RFS in MRDetect positive pts was 15.2 mths (range 3.7-33.4). Among 25 pts with no recurrence (median f/u 25.6 mths), MRDetect reported 4 pts to be MRD positive (specificity 84%). These results were consistent between EGFR mutated (sensitivity 86%, specificity 86%) and wildtype pts (sensitivity 82%, specificity 82%). For longitudinal samples (n=17 pts), negative ctDNA was associated with absence of recurrence in 14/15 pts (specificity 93%). At the AACR meeting, results from a planned larger validation study will be presented. Conclusion: Using a robust WGS implemented AI-based computational platform (MRDetect), we demonstrate high sensitivity and specificity detection of MRD in both EGFR mutated and wildtype NSCLC. With an increasing number of therapeutic options in the adjuvant setting for NSCLC, an ultra-sensitive MRD assay has the potential to facilitate personalized clinical decision-making for tailoring both the need and choice of adjuvant therapies. Citation Format: Aaron C. Tan, Stephanie P. Saw, Gillianne G. Lai, Kevin L. Chua, Angela Takano, Boon-Hean Ong, Tina P. Koh, Amit Jain, Wan Ling Tan, Quan Sing Ng, Ravindran Kanesvaran, Tanujaa Rajasekaran, Sunil Deochand, Dillon Maloney, Danielle Afterman, Tomer Lauterman, Noah Friedman, Imane Bourzgui, Nidhi Ramaraj, Zohar Donenhirsh, Ronel Veksler, Jonathan Rosenfeld, Ravi Kandasamy, Iman Tavassoly, Boris Oklander, Asaf Zviran, Wan-Teck Lim, Eng-Huat Tan, Anders J. Skanderup, Mei-Kim Ang, Daniel S. Tan. Ultra-sensitive detection of minimal residual disease (MRD) through whole genome sequencing (WGS) using an AI-based error suppression model in resected early-stage non-small cell lung cancer (NSCLC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5114.

Background: Neoadjuvant chemotherapy (NAC) followed by radical cystectomy (CX), is gold standard treatment in localized muscle-invasive bladder cancer (MIBC). About 45% of patients with MIBC develop metastatic relapse within 2 years after CX. The response rate to chemotherapy and immune checkpoint inhibitors (ICI) is relatively low, and biomarker tests for monitoring response are needed. Furthermore, biomarkers for early detection of minimal residual disease (MRD) after CX is needed to enable earlier treatment initiation. Tumor-informed detection of mutations in cell-free DNA (cfDNA) from peripheral blood has shown promising results in its ability to monitor MRD. However, the low tumor fraction after surgery and limited input material obtained from a typical plasma sample limits the probability of detecting low metastatic burden scenarios. Here we implemented and applied locally a whole-genome sequencing (WGS) approach to circulating tumor DNA (ctDNA) monitoring for improving ctDNA detection. Methods: A total of 140 MIBC patients undergoing NAC and CX were enrolled, including a test cohort (n=19) and a validation cohort (n=120). cfDNA was extracted from ~1mL plasma (n=1100) and procured from longitudinal plasma sampling during NAC (response measure), pre-cystectomy (response measure), post-surgery (relapse monitoring) and during immunotherapy (ICI treatment). WGS was applied to tumor/germline pairs (coverage >30x/20x) and plasma cfDNA (>20x) facilitating detection of genome wide genomic alterations and quantification of ctDNA using the MRDetect method. Results: We developed a personalized tumor-informed WGS model by integrating genome-wide mutation and copy number variation data coupled with advanced signal processing and AI-based error suppression. Patient-specific somatic variant patterns were then used for detecting and measuring the ctDNA levels in low-input blood samples by WGS. The assay sensitivity allowed for detection of tumor fractions down to 8*10-5. Furthermore, in our test cohort of 19 patients, we detected ctDNA after CX in 7 of 8 patients with clinical relapse (88% sensitivity) and detected no ctDNA in 11 of 11 patients with no clinical relapse (100% specificity). We observed a positive lead-time for MRD-based recurrence detection compared to CT-based reccurence detection (9 months on average). The full dataset is currently being processed and will be presented at the AACR 2022 meeting. Conclusions: For precision oncology, we need to develop quantitative and non-invasive methodologies to help tailor the treatments to individual patients and monitor them for further clinical decision-making. The results indicate the clinical potential of personalized genome-wide mutation integration as an ultra-sensitive, non-invasive method for MRD detection and treatment response monitoring which could aid in clinical management of patients with bladder cancer. Citation Format: Iver Nordentoft, Karin Birkenkamp-Demtröder, Emil Christensen, Sunil Deochand, Dillon Maloney, Danielle Afterman, Tomer Lauterman, Noah Friedman, Imane Bourzgui, Nidhi Ramaraj, Zohar Donenhirsh, Ronel Veksler, Sia Viborg, Mads Agerbæk, Jørgen Bjerggaard Jensen, Jonathan Rosenfeld, Ravi Kandasamy, Iman Tavassoly, Boris Oklander, Asaf Zviran, Lars Dyrskjøt. Genome-wide circulating tumor DNA for monitoring treatment response and metastatic relapse in bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 540.

e13582 Background: Minimal residual disease (MRD) monitoring using liquid biopsy for solid tumors requires a highly sensitive and specific assay that can overcome the limitation of low abundance cfDNA in a standard blood draw. We developed a whole-genome sequencing (WGS)-based assay to detect the presence of circulating tumor DNA (ctDNA) in plasma. The C2i assay is a tumor-informed assay that uses personalized tumor signature, advanced noise models, and artificial intelligence (AI) modalities to interrogate plasma for the presence of ctDNA longitudinally. Methods: The C2i test was developed in accordance with CAP/CLIA and New York state validation principles. We used contrived samples to establish analytical validation of the assay performance, which was then validated with a large clinical cohort of early-stage patients across various cancer types. Briefly, aggregated tumor signatures derived from cancer cell lines were fragmented and spiked into a contrived healthy plasma pool; the mixed samples were used to assess the presence of tumor DNA signature down to tumor fractions of 10e-4. Positive samples are identified by tumor-derived variants detected above the noise levels. Noise modeling was established using a panel of normal (PON) approach. We assessed the analytical sensitivity, specificity, and accuracy using 348 contrived samples derived from five different cancer cell lines. Reproducibility and precision were assessed with multiple replicates, and statistical concordance was reported. This validation was complemented by a cohort of 200 patients and ̃1000 plasma samples across a variety of cancer types including, NSCLC, MIBC, CRC, GBM, Breast Cancer, and a mixture of other cancer types. Results: Cancer cell lines, representing the five most prevalent disease indications, used for determining analytical sensitivity are as follows: CRC HT-29, Breast SK-BR3, Bladder HT-1376, Lung HCI-H526, and Prostate LNCaP. The cell line DNA was enzymatically fragmented and size-selected to mimic ctDNA. This ctDNA was spiked into cfDNA extracted from healthy volunteers at various dilution levels, varying from 10e0 to 10e-4. The 95% probability of detecting ctDNA was established at 10e-4. The reproducibility of tumor signature between replicates was assessed to be greater than 90%. The assay was performed using both normal and maximum input amounts. These performance estimates were then validated on a cohort of plasma collected from early-stage (stage I-III) patients across various cancer types. Conclusions: C2i MRD test is an ultrasensitive pan-cancer MRD monitoring assay used in several clinical trials across the world. We present an extensive analytical and clinical validation of the assay supporting its high performance.

e16527 Background: Bladder cancer (BC) is the 9th most commonly diagnosed cancer worldwide and each year responsible for 165,000 deaths. Neoadjuvant combination chemotherapy, followed by radical cystectomy, is used for the management of localized muscle-invasive bladder cancer. One of the critical challenges in this therapeutic regimen is monitoring the tumor load to assess therapeutic efficacy – this is typically performed by assessing pathological downstaging in the cystectomy specimen. A high frequency of patients presents with T0N0 at cystectomy (no indication of residual disease), and consequently, it is vital to investigate organ preservation approaches to identify those patients who may qualify for bladder preservation. For precision oncology, we need to develop quantitative and non-invasive diagnostic methodologies to help the oncologist tailor the treatments to individual patients and monitor them for further clinical decision-making. Methods: Cell-free DNA (cfDNA) mutation detection has shown significant promise in its ability to monitor minimal residual disease and disease relapse by detection of cancer mutations in the peripheral blood. However, the combination of low tumor fraction and limited input material obtained from a typical plasma sample restricts the probability of detecting low metastatic burden in cfDNA through current deep targeted sequencing methods. Results: Here we present results from applying whole-genome sequencing (WGS) of cfDNA. We integrate a genome-wide mutation and copy number monitoring approach coupled with advanced signal processing and Artificial Intelligence (AI) for measuring the tumor load from low-input blood samples (̃1mL of plasma) with ultra-sensitive detection. The increased sensitivity allowed clinical detection of tumor fraction down to 8*10-5 and recurrence detection sensitivity achieving > 65% at the first two months post-surgery. The WGS cfDNA approach is being evaluated on a patient cohort of more than 50 bladder cancer patients with longitudinal plasma sampling during neoadjuvant chemotherapy (response measure), pre-cystectomy (complete response measure), and post-surgery (relapse monitoring). Conclusions: The results indicate the clinical potential of genome-wide mutation integration as an ultra-sensitive, non-invasive diagnostic method for bladder cancer clinical management and bladder organ preservation.

Background: Checkpoint blockade therapies like PD-1 antibodies elicit durable long-lasting immunity in a subset of patients of certain tumor types. However, many patients across a range of tumor types are resistant to checkpoint blockade. Mechanisms that confer local response or resistance to checkpoint blockade are not well understood. Mounting evidence points to local suppression of T cell function as one of the most substantial barriers to effective antitumor immunity. Methods: The study involved multiparametric flow cytometry and genomic characterization of a subset of T cells in the tumors and lymphoid organs of syngeneic tumors, genetically engineered mouse model of cancers and human tumors. Results: A significant fraction (10-40%) of α/β TCR+ CD3+ T cells do not express CD4, CD8 or NKp46 in the tumors. The presence of double-negative T-cell subset (DN T cells) is restricted to tumor microenvironment and is relatively scarce in tumor draining lymph nodes and in spleen. To identify if DN T cells are antigen-specific, we performed AH-1 tetramer staining. While a substantial fraction of CD8 T cells are AH-1 tetramer positive, majority of DN T cells are AH-1 tetramer negative in CT26 tumors. Recently, it has been shown that higher frequency of CD39-negative bystander T cells correlated to lack of response to PD-1 therapy in non-small cell lung cancer patients. Mounting evidence also reveals presence of a specific subset of CD8 T cells with features of stem cell memory in tumors as defined by CXCR5 and TCF1 expression. Efforts are under way to understand if DN T cells exhibit bystander cell and/or memory stem-like phenotype. Majority of the DN T cells are proliferating (Ki67+) and express very low levels of PD-1 (in contrast to CD8 T cells) and Granzyme B. Treatment of mice bearing syngeneic tumors with PD-1 checkpoint blockade therapy does not impact the frequency of DN T-cell subset consistent with lower levels of PD-1 expression. Moreover, a substantial frequency (30-40%) of DN T cells in both syngeneic and KPC pancreatic GEMM tumors express CD103, a tissue resident marker. Furthermore, DN T cells are CD44+ CD127+ KLRG1- and may represent a memory precursor cell population. Upon ex vivo stimulation, these DN T cell subsets proliferate and express modest levels of PD-1. Preliminary analysis of single-cell RNA sequencing data from FACS sorted murine DN T cells reveals lack of CD4, CD8 expression and retention of CD2, CD44, CD69, CCR7 and CXCR5 expression. Flow cytometry analysis of human CD2+ TILs reveals presence of DN T cells in human tumors. Single-cell transcriptome analysis of CD2+ T cells isolated from human colorectal tumors revealed presence of DN T cells. Current efforts are focused on further characterization of this subset in both mouse and human tumors. Conclusions: In this study, we describe a tumor-resident CD4 and CD8 double-negative T-cell subset that may represent a bystander cell population with features of memory precursors and potential implications in modulation of response to checkpoint blockade therapy in cancer. Citation Format: Murali Gururajan, Ravi Kandasamy, Jessica Wong, Kalpit Shah, Shuoguo Wang, Adam Bata, Amy Truong, Sunil Kuppasani, Ching-Ping Ho, Robert Graziano, Michael Quigley, Anwar Murtaza, Jinqi Liu. High-dimensional analysis of tumor-resident CD4 and CD8 double-negative T-cell subset in multiple tumor types [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr B61.

Flip chip ball grid array (FC-BGA) packages are commonly used for high inputs/outputs (I/O) ICs; they have been proven to provide good solutions for a variety of applications to maximize thermal and electrical performance. A fundamental limitation to such devices is the thermal resistance at the top of the package, which is characterized θ JC parameter. The die-to-lid interface thermal resistance is identified as a critical issue for the thermal management of electronic packages. This paper focuses on the effect of the interface material property changes on the interface thermal resistance. The effect of package’s junction to case (Theta-JC or θ JC ) thermal performance is investigated for bare die, flat lid and cup lid packages using a validated thermal model. Thermal performance of a cup or flat lid attached and bare die packages were investigated for different interface materials. Improved Theta-JC performance was observed for the large die as compared to the smaller die. Several parametric studies were carried out to understand the effects of interface bond line thickness (BLT), different die sizes, the average void size during assembly and thermal conductivity of interface materials on package thermal resistance.

PurposeIn the semiconductor electronics industry, effective heat removal from the integrated circuits (IC) chip, through the electronic package to the environment is crucial to maintain an allowable junction temperature of the IC chip. Thermal performances of such electronic packages are characterized by package thermal resistance called θ‐JA and are widely used in the electronic industry. Improving thermal performance is numerically predicted using computational fluid dynamics (CFD) technique and experimental tests are carried out to verify the numerical predictions. To provide new/additional data and demonstrate CFD technique for thermal characterization of electronic packages with experimental results.Design/methodology/approachThe thermal performance of electronic packages has been studied using a CFD technique. The finite volume method is a technique used for solving a set of partial differential equations in a domain, using control volume based discretization. A detailed thermal model of an electronic package was created using a CFD tool and validated against the experimental data obtained in a natural convection environment, compliant to JEDEC standards. The thermal performance of the package was evaluated for different die sizes and epoxy molding compounds at different power levels. The use of a heat slug was investigated to identify its effect on heat dissipation for the future generations of IC, which are expected to be smaller in size and to dissipate more power. Free convective flow velocities, detailed temperature and heat flow distributions around the package will also be presented.FindingsThe study demonstrates that applying CFD techniques can provide accurate results on estimating thermal characterization of an electronic package. Predicted device junction temperatures as well as the thermal resistance of packages can be predicted with a good accuracy for different ranges of power levels in natural convection. The numerically estimated die junction temperatures have also been found to be accurate and reliable.Research limitations/implicationsThe analysis is limited to an incompressible fluid. The effect of forced convection is not considered.Practical implicationsNew and additional generated data will be helpful in the design and decision making time of the product to choose a low cost and viable thermal performance solution in the cooling of electronic components at low power.Originality/valueThe electronic package involves multi‐material and applying CFD technique is useful to determine the accurate thermal performance and simple and fast to apply for different conditions/material sets. Predictions of junction‐to‐ambient thermal resistance and device junction temperature values are compared against measurements. Excellent correlation was obtained. The results thus obtained compare well with the experimental results, but the computational effort and time required in the analysis is much small as compared.